Why FPGA
•
1 like•88 views
The document discusses implementing computer vision algorithms using OpenCV on an FPGA. Specifically, it explores a stitching algorithm for biomedical applications. The algorithm involves capturing images, extracting features, selecting features, matching features, warping, blending, and merging images. It notes that this algorithm is embarrassingly parallel and well-suited for an FPGA implementation. It then profiles the different steps and discusses tools like OpenCV, OpenCL, and SDAccel for FPGA programming. Current implementations using OpenCV and OpenCL on a Xilinx FPGA are also mentioned. Contact information is provided for the presenters.
Report
Share
Report
Share
Download to read offline
Recommended
Single layer perceptron in python
This document discusses neural networks and single layer perceptrons. It provides an overview of biological neurons versus artificial neurons in neural networks. It then explains the computational steps for training a single layer perceptron, including calculating the activation, using an activation function, and updating weights with gradient descent. The document demonstrates implementing a perceptron model in Python to classify data from the Sonar dataset. It evaluates the model using metrics like a confusion matrix and accuracy.
Anomaly Detection using Deep Auto-Encoders | Gianmario Spacagna
One of the determinants for a good anomaly detector is finding smart data representations that can easily evince deviations from the normal distribution. Traditional supervised approaches would require a strong assumption about what is normal and what not plus a non negligible effort in labeling the training dataset. Deep auto-encoders work very well in learning high-level abstractions and non-linear relationships of the data without requiring data labels. In this talk we will review a few popular techniques used in shallow machine learning and propose two semi-supervised approaches for novelty detection: one based on reconstruction error and another based on lower-dimensional feature compression.
Automatic selection of object recognition methods using reinforcement learning
The document discusses using reinforcement learning to automatically select between two object recognition methods. The goal is for a robot to decide which method to use depending on current conditions. It describes using Q-learning to choose between Lowe's feature matching or a vocabulary tree algorithm. State is defined based on image attributes, and actions update the value of state-action pairs to select the best recognition method.
A R T I F I C I A L N E U R A L N E T W O R K S J N T U M O D E L P A P ...
This document contains 4 sets of question papers for a JNTU-IV B.Tech Artificial Neural Networks exam from February 2008 and February 2007. Each set contains 8 multiple choice or short answer questions testing students' knowledge of topics like perceptrons, learning algorithms, radial basis networks, associative memory, applications of neural networks, etc. The questions are similar across the 4 sets but with some variations in wording or examples used.
Uncertainty-wise Engineering of IoT Cloud Systems
From system models to non-functional analyses, deployment, and testing.
Talk given at https://cdl-mint.big.tuwien.ac.at/mde4iot2017/
Taras Lehinevych "Shadows Generation in the Wild"
The presence of strong illumination variations in images, shadows, in particular, have been shown to be problematic for a variety of computer vision algorithms such as object recognition and recognition.
We'll briefly talk about shadow detection, removal and focus on shadow generation in the wild for data augmentation.
Website: https://fwdays.com/en/event/data-science-fwdays-2019/review/shadows-generation-in-the-wild
Work organization
The document discusses implementing computer vision algorithms using OpenCV on an FPGA. It describes implementing a stitching algorithm for biomedical applications both on an Intel Atom processor and on an AlphaData Kintex Ultrascale FPGA integrated on an Intel base board. The main tasks discussed are algorithm analysis, code profiling, kernel implementation on the FPGA, host integration, and performance analysis. Implementation responsibilities are assigned to different team members, with Matteo Foglio and Andrea Milanta focusing on the Intel Atom implementation and Guido Muscioni focusing on the FPGA implementation. Potential strengths, weaknesses, opportunities, and threats of the FPGA approach are also summarized.
A FRIENDLY APPROACH TO PARTICLE FILTERS IN COMPUTER VISION
This is a friendly approach to particle filters. Some hints, examples, and good practices to be able to successfully apply particle filters to solve your computer vision pro
Recommended
Single layer perceptron in python
This document discusses neural networks and single layer perceptrons. It provides an overview of biological neurons versus artificial neurons in neural networks. It then explains the computational steps for training a single layer perceptron, including calculating the activation, using an activation function, and updating weights with gradient descent. The document demonstrates implementing a perceptron model in Python to classify data from the Sonar dataset. It evaluates the model using metrics like a confusion matrix and accuracy.
Anomaly Detection using Deep Auto-Encoders | Gianmario Spacagna
One of the determinants for a good anomaly detector is finding smart data representations that can easily evince deviations from the normal distribution. Traditional supervised approaches would require a strong assumption about what is normal and what not plus a non negligible effort in labeling the training dataset. Deep auto-encoders work very well in learning high-level abstractions and non-linear relationships of the data without requiring data labels. In this talk we will review a few popular techniques used in shallow machine learning and propose two semi-supervised approaches for novelty detection: one based on reconstruction error and another based on lower-dimensional feature compression.
Automatic selection of object recognition methods using reinforcement learning
The document discusses using reinforcement learning to automatically select between two object recognition methods. The goal is for a robot to decide which method to use depending on current conditions. It describes using Q-learning to choose between Lowe's feature matching or a vocabulary tree algorithm. State is defined based on image attributes, and actions update the value of state-action pairs to select the best recognition method.
A R T I F I C I A L N E U R A L N E T W O R K S J N T U M O D E L P A P ...
This document contains 4 sets of question papers for a JNTU-IV B.Tech Artificial Neural Networks exam from February 2008 and February 2007. Each set contains 8 multiple choice or short answer questions testing students' knowledge of topics like perceptrons, learning algorithms, radial basis networks, associative memory, applications of neural networks, etc. The questions are similar across the 4 sets but with some variations in wording or examples used.
Uncertainty-wise Engineering of IoT Cloud Systems
From system models to non-functional analyses, deployment, and testing.
Talk given at https://cdl-mint.big.tuwien.ac.at/mde4iot2017/
Taras Lehinevych "Shadows Generation in the Wild"
The presence of strong illumination variations in images, shadows, in particular, have been shown to be problematic for a variety of computer vision algorithms such as object recognition and recognition.
We'll briefly talk about shadow detection, removal and focus on shadow generation in the wild for data augmentation.
Website: https://fwdays.com/en/event/data-science-fwdays-2019/review/shadows-generation-in-the-wild
Work organization
The document discusses implementing computer vision algorithms using OpenCV on an FPGA. It describes implementing a stitching algorithm for biomedical applications both on an Intel Atom processor and on an AlphaData Kintex Ultrascale FPGA integrated on an Intel base board. The main tasks discussed are algorithm analysis, code profiling, kernel implementation on the FPGA, host integration, and performance analysis. Implementation responsibilities are assigned to different team members, with Matteo Foglio and Andrea Milanta focusing on the Intel Atom implementation and Guido Muscioni focusing on the FPGA implementation. Potential strengths, weaknesses, opportunities, and threats of the FPGA approach are also summarized.
A FRIENDLY APPROACH TO PARTICLE FILTERS IN COMPUTER VISION
This is a friendly approach to particle filters. Some hints, examples, and good practices to be able to successfully apply particle filters to solve your computer vision pro
How to break apart a monolithic system safely without destroying your team - ...
How to break apart a monolithic system safely without destroying your team - talk at Velocity Eu Amsterdam on 7 Nov 2016
You'll learn some team-first heuristics to use when decomposing large or monolithic software into smaller pieces.
http://conferences.oreilly.com/velocity/devops-web-performance-eu/public/schedule/detail/52879
Teams and monoliths - Matthew Skelton - Velocity EU 2016
How to break apart a monolithic system safely without destroying your team - talk at Velocity Eu Amsterdam on 7 Nov 2016
You'll learn some team-first heuristics to use when decomposing large or monolithic software into smaller pieces.
http://conferences.oreilly.com/velocity/devops-web-performance-eu/public/schedule/detail/52879
FOCus Introduction
The document discusses a project to implement computer vision algorithms using OpenCV on an FPGA. Specifically, it focuses on optimizing an image stitching algorithm to reduce processing time and improve quality. It identifies using an Intel Atom processor board paired with an AlphaData Kintex Ultrascale FPGA to maximize parallelization opportunities for image manipulation algorithms. The goal is to overcome speed limitations of the Intel Atom by offloading work to the FPGA, which will involve analyzing and optimizing the OpenCV stitching algorithm for parallel hardware implementation.
Teams and monoliths - Matthew Skelton - Agile in the City Bristol 2016
Teams and monoliths - Matthew Skelton - Agile in the City Bristol 2016Skelton Thatcher Consulting Ltd
1. The document provides a recipe for breaking apart a monolithic software system into microservices without overloading development teams.
2. The recipe involves instrumenting the monolith to understand data flows, aligning team boundaries with natural segments of the code, and splitting the system into independent services one segment at a time.
3. The goal is to reduce cognitive load on development teams by separating codebases, deployments, and responsibilities into independent subsystems that match team capabilities and domains of expertise.The BondMachine: a fully reconfigurable computing ecosystem
The aim of the BondMachine (BM) project is to implement a computing system to enable a real and full exploitation of the underlying hardware. This is a key to the success in the era of hybrid computing. In order to achieve this objective the BM has been designed to create a heterogeneous and flexible architecture on top of FPGAs. Moreover the overall vision is based on a reduction of the number of hardware/software layers which by product guarantees a simpler software development. As such, the BM project has been thought as a complete reconfigurable computing ecosystem that, starting from a high-level description, creates both the hardware and the software that runs on it.
The two architectural pillars are computing elements (processors) and non-computing elements (for example memories, channels, barriers). The latter are meant to be shared among processors. Finally, thanks to a custom network protocol, many BondMachines can be interconnected together, therefore building heterogeneous multi-core systems or even clusters of multi-cores.
The flexibility of the BM makes possible the implementation of any computing system ranging from networks of small agents, like IoT (Internet of Things), to high-performance devices for ML (Machine Learning) or real time data analysis, and even systems that mix all this different characteristics together. The BM can interact with standard Linux workstations both as a special purpose hardware accelerator or as part of a computer/BM hybrid clusters.
HAMS - Product and Prototype
HAMS project: update of our work scheduling at April 4th, with description of our product and our future prototype!
final presentation
This document outlines a student project involving digital image processing techniques. The project aims to 1) evaluate different image de-noising techniques using simulated data, 2) design a system to process and register brain CT and MR images, and 3) compare medical image registration and fusion techniques. The document describes simulating various types of noise, using spatial and wavelet-based filters to reduce noise, and evaluating the performance of registration and fusion algorithms. Chapters will address noise reduction, registration foundations, biomedical applications, and fusion methods.
Foreground algorithms for detection and extraction of an object in multimedia...
Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.
VTT For Industry
Technology industries have a very important direct and indirect impact on Finnish business life now and also in the future. A remarkable potential lies particularly in the small- and medium-sized enterprises. To develop and maintain industrial competitiveness we develop technological solutions which can widely be exploited by the Finnish manufacturing industries.
This presentation gives an overview of the VTT’s experience and offering for industry and is focused to computational material development, robotics, additive manufacturing, and concept design.
DEFENSE
This document provides an overview of algorithmic issues in computational intelligence optimization from design to implementation. It discusses key concepts in optimization problems including analytical approaches, exact methods, approximate iterative methods, and metaheuristics. It also examines challenges in optimizing real-world problems that are highly non-linear, multi-modal, computationally expensive, and have memory/time constraints. The document concludes by discussing the need for algorithms to balance exploration and exploitation and to adapt to problem landscapes.
Suspicious Activity Detection
Uses OpenCV and NumPy modules.
Detects unusual behavior via the available dataset.
Machine Learning Concept.
System Security @ NECSTLab
Research in current and future cybersecurity threats at the NECSTLab is heavily centered on experimentally analyzing real systems, with a focus on a data-driven approach. In this context, in our lab we are pursuing four lines of research: large scale and automated malware analysis, detection of financial frauds through machine learning, mobile security and mobile malware analysis, as well as cyber-physical security, where we focus on automotive network and on the security of the so-called Industry 4.0 paradigm. In this talk, we will give a bird’s eye view on the system security research at the NECSTLab, presenting the rationale of our research as well as introducing representative projects in our four lines of research and the main results we achieved.
Horizontal Requirement Engineering in Integration of Multiple IoT Use Cases o...
SecureEdge2017 (CIT 2017 workshop) presentation
version a1708talk secureedge-cpaas-horizontal-requirement-engineering-170823
Lecture-1-2-+(1).pdf
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also lists the top 10 computer vision tools for 2020 and discusses negative results in computer vision research.
Lecture-1-2-+(1).pdf
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also discusses sources of noise in images, performance metrics like mean square error and confusion matrices, and some top computer vision tools like OpenCV, TensorFlow, Keras and YOLO.
K0445660
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Mtech First progress PRESENTATION ON VIDEO SUMMARIZATION
This document summarizes Neeraj Baghel's first progress presentation on video summarization. It discusses key aspects of video summarization such as types (key frame extraction and video skims), applications (browsing recorded content, databases, surveillance), challenges (information loss, computation cost, performance evaluation), tools, datasets, conferences, and researchers. The presentation outlines techniques for intelligently summarizing lengthy videos to capture the essence and remove redundant information.
IRJET- Object Detection in an Image using Convolutional Neural Network
This document summarizes a research paper on object detection in images using convolutional neural networks. The paper proposes using the ImageAI Python library along with a region-based convolutional neural network model to perform object detection. The methodology loads a pre-trained model, imports the ImageAI detection class, detects objects in an input image, and prints the detected objects and probabilities. The system can accurately detect objects like faces and vehicles from images and has applications in security and traffic monitoring. However, training the neural network requires a large dataset and takes a long time.
PhD Welcome Day 2014
The document discusses the author's background and experience obtaining a PhD. It describes him studying computer science and working as a bartender before joining a software engineering unit. He then obtained a master's degree and joined a PhD program in 2009, receiving his PhD in 2013 with a thesis titled "Security Testing of Web and Smartphone Applications." It also includes illustrations about the process of obtaining a PhD and expanding human knowledge, as well as lists publications and conferences the author participated in during his PhD.
Voice Enable Blind Assistance System -Real time Object Detection
This document describes a voice-enabled blind assistance system using real-time object detection. The system uses a Single Shot Multi-Box Detection (SSD) model with MobileNet to detect objects in frames captured by a webcam in real-time. When an object is detected, its class is converted to speech using text-to-speech and provided to blind users along with alerts if the object is too close. The system aims to help visually impaired people gain more independence by identifying objects and hazards in their environment. An experiment showed the SSD MobileNet model achieved accurate real-time detection of household objects.
Software Engineering and Project Management - Introduction, Modeling Concepts...
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
More Related Content
Similar to Why FPGA
How to break apart a monolithic system safely without destroying your team - ...
How to break apart a monolithic system safely without destroying your team - talk at Velocity Eu Amsterdam on 7 Nov 2016
You'll learn some team-first heuristics to use when decomposing large or monolithic software into smaller pieces.
http://conferences.oreilly.com/velocity/devops-web-performance-eu/public/schedule/detail/52879
Teams and monoliths - Matthew Skelton - Velocity EU 2016
How to break apart a monolithic system safely without destroying your team - talk at Velocity Eu Amsterdam on 7 Nov 2016
You'll learn some team-first heuristics to use when decomposing large or monolithic software into smaller pieces.
http://conferences.oreilly.com/velocity/devops-web-performance-eu/public/schedule/detail/52879
FOCus Introduction
The document discusses a project to implement computer vision algorithms using OpenCV on an FPGA. Specifically, it focuses on optimizing an image stitching algorithm to reduce processing time and improve quality. It identifies using an Intel Atom processor board paired with an AlphaData Kintex Ultrascale FPGA to maximize parallelization opportunities for image manipulation algorithms. The goal is to overcome speed limitations of the Intel Atom by offloading work to the FPGA, which will involve analyzing and optimizing the OpenCV stitching algorithm for parallel hardware implementation.
Teams and monoliths - Matthew Skelton - Agile in the City Bristol 2016
Teams and monoliths - Matthew Skelton - Agile in the City Bristol 2016Skelton Thatcher Consulting Ltd
1. The document provides a recipe for breaking apart a monolithic software system into microservices without overloading development teams.
2. The recipe involves instrumenting the monolith to understand data flows, aligning team boundaries with natural segments of the code, and splitting the system into independent services one segment at a time.
3. The goal is to reduce cognitive load on development teams by separating codebases, deployments, and responsibilities into independent subsystems that match team capabilities and domains of expertise.The BondMachine: a fully reconfigurable computing ecosystem
The aim of the BondMachine (BM) project is to implement a computing system to enable a real and full exploitation of the underlying hardware. This is a key to the success in the era of hybrid computing. In order to achieve this objective the BM has been designed to create a heterogeneous and flexible architecture on top of FPGAs. Moreover the overall vision is based on a reduction of the number of hardware/software layers which by product guarantees a simpler software development. As such, the BM project has been thought as a complete reconfigurable computing ecosystem that, starting from a high-level description, creates both the hardware and the software that runs on it.
The two architectural pillars are computing elements (processors) and non-computing elements (for example memories, channels, barriers). The latter are meant to be shared among processors. Finally, thanks to a custom network protocol, many BondMachines can be interconnected together, therefore building heterogeneous multi-core systems or even clusters of multi-cores.
The flexibility of the BM makes possible the implementation of any computing system ranging from networks of small agents, like IoT (Internet of Things), to high-performance devices for ML (Machine Learning) or real time data analysis, and even systems that mix all this different characteristics together. The BM can interact with standard Linux workstations both as a special purpose hardware accelerator or as part of a computer/BM hybrid clusters.
HAMS - Product and Prototype
HAMS project: update of our work scheduling at April 4th, with description of our product and our future prototype!
final presentation
This document outlines a student project involving digital image processing techniques. The project aims to 1) evaluate different image de-noising techniques using simulated data, 2) design a system to process and register brain CT and MR images, and 3) compare medical image registration and fusion techniques. The document describes simulating various types of noise, using spatial and wavelet-based filters to reduce noise, and evaluating the performance of registration and fusion algorithms. Chapters will address noise reduction, registration foundations, biomedical applications, and fusion methods.
Foreground algorithms for detection and extraction of an object in multimedia...
Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.
VTT For Industry
Technology industries have a very important direct and indirect impact on Finnish business life now and also in the future. A remarkable potential lies particularly in the small- and medium-sized enterprises. To develop and maintain industrial competitiveness we develop technological solutions which can widely be exploited by the Finnish manufacturing industries.
This presentation gives an overview of the VTT’s experience and offering for industry and is focused to computational material development, robotics, additive manufacturing, and concept design.
DEFENSE
This document provides an overview of algorithmic issues in computational intelligence optimization from design to implementation. It discusses key concepts in optimization problems including analytical approaches, exact methods, approximate iterative methods, and metaheuristics. It also examines challenges in optimizing real-world problems that are highly non-linear, multi-modal, computationally expensive, and have memory/time constraints. The document concludes by discussing the need for algorithms to balance exploration and exploitation and to adapt to problem landscapes.
Suspicious Activity Detection
Uses OpenCV and NumPy modules.
Detects unusual behavior via the available dataset.
Machine Learning Concept.
System Security @ NECSTLab
Research in current and future cybersecurity threats at the NECSTLab is heavily centered on experimentally analyzing real systems, with a focus on a data-driven approach. In this context, in our lab we are pursuing four lines of research: large scale and automated malware analysis, detection of financial frauds through machine learning, mobile security and mobile malware analysis, as well as cyber-physical security, where we focus on automotive network and on the security of the so-called Industry 4.0 paradigm. In this talk, we will give a bird’s eye view on the system security research at the NECSTLab, presenting the rationale of our research as well as introducing representative projects in our four lines of research and the main results we achieved.
Horizontal Requirement Engineering in Integration of Multiple IoT Use Cases o...
SecureEdge2017 (CIT 2017 workshop) presentation
version a1708talk secureedge-cpaas-horizontal-requirement-engineering-170823
Lecture-1-2-+(1).pdf
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also lists the top 10 computer vision tools for 2020 and discusses negative results in computer vision research.
Lecture-1-2-+(1).pdf
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also discusses sources of noise in images, performance metrics like mean square error and confusion matrices, and some top computer vision tools like OpenCV, TensorFlow, Keras and YOLO.
K0445660
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Mtech First progress PRESENTATION ON VIDEO SUMMARIZATION
This document summarizes Neeraj Baghel's first progress presentation on video summarization. It discusses key aspects of video summarization such as types (key frame extraction and video skims), applications (browsing recorded content, databases, surveillance), challenges (information loss, computation cost, performance evaluation), tools, datasets, conferences, and researchers. The presentation outlines techniques for intelligently summarizing lengthy videos to capture the essence and remove redundant information.
IRJET- Object Detection in an Image using Convolutional Neural Network
This document summarizes a research paper on object detection in images using convolutional neural networks. The paper proposes using the ImageAI Python library along with a region-based convolutional neural network model to perform object detection. The methodology loads a pre-trained model, imports the ImageAI detection class, detects objects in an input image, and prints the detected objects and probabilities. The system can accurately detect objects like faces and vehicles from images and has applications in security and traffic monitoring. However, training the neural network requires a large dataset and takes a long time.
PhD Welcome Day 2014
The document discusses the author's background and experience obtaining a PhD. It describes him studying computer science and working as a bartender before joining a software engineering unit. He then obtained a master's degree and joined a PhD program in 2009, receiving his PhD in 2013 with a thesis titled "Security Testing of Web and Smartphone Applications." It also includes illustrations about the process of obtaining a PhD and expanding human knowledge, as well as lists publications and conferences the author participated in during his PhD.
Voice Enable Blind Assistance System -Real time Object Detection
This document describes a voice-enabled blind assistance system using real-time object detection. The system uses a Single Shot Multi-Box Detection (SSD) model with MobileNet to detect objects in frames captured by a webcam in real-time. When an object is detected, its class is converted to speech using text-to-speech and provided to blind users along with alerts if the object is too close. The system aims to help visually impaired people gain more independence by identifying objects and hazards in their environment. An experiment showed the SSD MobileNet model achieved accurate real-time detection of household objects.
Similar to Why FPGA (20)
How to break apart a monolithic system safely without destroying your team - ...
How to break apart a monolithic system safely without destroying your team - ...
Teams and monoliths - Matthew Skelton - Velocity EU 2016
Teams and monoliths - Matthew Skelton - Velocity EU 2016
Teams and monoliths - Matthew Skelton - Agile in the City Bristol 2016
Teams and monoliths - Matthew Skelton - Agile in the City Bristol 2016
The BondMachine: a fully reconfigurable computing ecosystem
The BondMachine: a fully reconfigurable computing ecosystem
Foreground algorithms for detection and extraction of an object in multimedia...
Foreground algorithms for detection and extraction of an object in multimedia...
Horizontal Requirement Engineering in Integration of Multiple IoT Use Cases o...
Horizontal Requirement Engineering in Integration of Multiple IoT Use Cases o...
Mtech First progress PRESENTATION ON VIDEO SUMMARIZATION
Mtech First progress PRESENTATION ON VIDEO SUMMARIZATION
IRJET- Object Detection in an Image using Convolutional Neural Network
IRJET- Object Detection in an Image using Convolutional Neural Network
Voice Enable Blind Assistance System -Real time Object Detection
Voice Enable Blind Assistance System -Real time Object Detection
Recently uploaded
Software Engineering and Project Management - Introduction, Modeling Concepts...
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
22CYT12-Unit-V-E Waste and its Management.ppt
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Hematology Analyzer Machine - Complete Blood Count
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
AI assisted telemedicine KIOSK for Rural India.pptx
It gives the overall description of SIH problem statement " AI assisted telemedicine KIOSK for Rural India".
cnn.pptx Convolutional neural network used for image classication
Convolutional Neural Network used for image classification
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
CalArts毕业证学历书【微信95270640】CalArts毕业证’圣力嘉学院毕业证《Q微信95270640》办理CalArts毕业证√文凭学历制作{CalArts文凭}购买学历学位证书本科硕士,CalArts毕业证学历学位证【实体公司】办毕业证、成绩单、学历认证、学位证、文凭认证、办留信网认证、（网上可查，实体公司，专业可靠）
(诚招代理)办理国外高校毕业证成绩单文凭学位证,真实使馆公证（留学回国人员证明）真实留信网认证国外学历学位认证雅思代考国外学校代申请名校保录开请假条改GPA改成绩ID卡
1.高仿业务:【本科硕士】毕业证,成绩单（GPA修改）,学历认证（教育部认证）,大学Offer,,ID,留信认证,使馆认证,雅思,语言证书等高仿类证书；
2.认证服务: 学历认证（教育部认证）,大使馆认证（回国人员证明）,留信认证（可查有编号证书）,大学保录取,雅思保分成绩单。
3.技术服务：钢印水印烫金激光防伪凹凸版设计印刷激凸温感光标底纹镭射速度快。
办理加利福尼亚艺术学院加利福尼亚艺术学院毕业证文凭证书流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）
-办理真实使馆公证（即留学回国人员证明）
-办理各国各大学文凭（世界名校一对一专业服务,可全程监控跟踪进度）
-全套服务：毕业证成绩单真实使馆公证真实教育部认证。让您回国发展信心十足！
（详情请加一下 文凭顾问+微信:95270640）欢迎咨询！子小伍玩小伍比山娃小一岁虎头虎脑的很霸气父亲让山娃跟小伍去夏令营听课山娃很高兴夏令营就设在附近一所小学山娃发现那所小学比自己的学校更大更美操场上还铺有塑胶跑道呢里面很多小朋友一班一班的快快乐乐原来城里娃都藏这儿来了怪不得平时见不到他们山娃恍然大悟起来吹拉弹唱琴棋书画山娃都不懂却什么都想学山娃怨自己太笨什么都不会斟酌再三山娃终于选定了学美术当听说每月要交元时父亲犹豫了山娃也说爸算了吧咱学校一学期才转
Comparative analysis between traditional aquaponics and reconstructed aquapon...
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
For International shipping and maritime laws all wood must contain the ISPM 15 Stamp. Here is how and why.
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
原版一模一样【微信：741003700 】【美国密歇根州立大学毕业证学位证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Slides for the 4th Presentation on LLM Fine-Tuning with QLoRA Presented by Anant, featuring DataStax Astra
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering PROJECT REPORT ON SUMMER VOCATIONAL TRAINING
AT MBB AIRPORT
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Null Bangalore | Pentesters Approach to AWS IAM
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Recently uploaded (20)
Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
Hematology Analyzer Machine - Complete Blood Count
Hematology Analyzer Machine - Complete Blood Count
AI assisted telemedicine KIOSK for Rural India.pptx
AI assisted telemedicine KIOSK for Rural India.pptx
cnn.pptx Convolutional neural network used for image classication
cnn.pptx Convolutional neural network used for image classication
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdf
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Why FPGA
- 1. Andrea Milanta (andrea.milanta@mail.polimi.it) Guido Muscioni (guido.muscioni@mail.polimi.it) Matteo Foglio (matteo.foglio@mail.polimi.it) Computer vision implementing OpenCV on FPGA 1 Seminar Room (Politecnico di Milano) 05/04/2017
- 2. Introduction 2 AlphaData Kintex Ultrascale FPGAIntel base board Intel Atom E8000 Stitching algorithm for biomedical application VS
- 3. Embarassingly parallel 3 ”An embarrassingly parallel workload or problem is one where little or no effort is needed to separate the problem into a number of parallel tasks. ” Task(3)Task(2)Task(1) … Task(n) Problem
- 4. Capturing and Matching 4 Capturing Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 5. Filtering Capturing and Matching 4 Capturing Features extraction Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 6. Filtering Features selection Capturing and Matching 4 Capturing Features extraction Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 7. Filtering Features selection Features matching Capturing and Matching 4 Capturing Features extraction Multiple comparisons Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 8. Filtering Features selection Features matching Capturing and Matching 4 Capturing Features extraction Multiple comparisons Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 9. Merging (with blending) 5 Merging Warping Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 10. Merging (with blending) 5 Merging Warping Blending Filtering Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 11. Merging (with blending) 5 Merging Warping Blending Filtering Images from: http://matthewalunbrown.com/papers/ijcv2007.pdf
- 13. Profiling 6 ++ 50-90% 10-40% KPI: execution time Features extraction Features matching Blending Merging
- 14. Tools 7 OpenCV
- 19. Current implementations 8 OpenCV Images from: https://www.xilinx.com/video/corporate/ai-eye-tracking-technology.html
- 20. Current implementations 8 cv::ocl OpenCV OpenCL powered by Xilinx Images from: https://www.xilinx.com/video/corporate/ai-eye-tracking-technology.html
- 21. Questions? Guido Muscioni Bachelor in Computer Science guido.muscioni@mail.polimi.it Andrea Milanta Bachelor in Computer Science andrea.milanta@mail.polimi.it FOCus at NECST facebook.com/FOCusatNECST/ FOCusAtNECST slideshare.net/FOCusAtNECST/ @FOCusAtNECST twitter.com/FOCusAtNECST 9 Matteo Foglio Bachelor in Computer Science matteo.foglio@mail.polimi.it Contact us bitbucket.org/necst/xohw17_f ocus_public