This document describes a proposed traffic sign recognition and voice alert system using convolutional neural networks. The system is designed to identify traffic signs using a CNN model trained on image datasets, then provide an audible alert to notify drivers. It aims to improve safety by ensuring drivers are aware of traffic signs. The system design involves collecting image data, training the CNN model to classify sign types, detecting signs in new images using the model, and triggering voice alerts for recognized signs. Testing showed the system could accurately perform registration, login, image uploading, model training, and sign detection/alerts as intended. The system is intended to help drivers follow traffic rules and make informed decisions to increase safety.
The project is about building a human-computer interaction system
using hand gesture by cheap alternative to depth camera. We present
a robust , efficient and real-time technique for depth mapping using
normal 2D -camera and Infrared LED arrays . We use HOG feature
based SVM classifiers to predict hand pose and dynamic hand gestures . The system also tracks hand movements and events like grabbing and
clicking bythe hand.
The project is about building a human-computer interaction system
using hand gesture by cheap alternative to depth camera. We present
a robust , efficient and real-time technique for depth mapping using
normal 2D -camera and Infrared LED arrays . We use HOG feature
based SVM classifiers to predict hand pose and dynamic hand gestures . The system also tracks hand movements and events like grabbing and
clicking bythe hand.
The fear of touching public surfaces sparked by the Covid -19 outbreak is spurring a shift from fingerprint sensors to Facial Recognition Systems for allowing access to employees across offices in India.
Face recognition is a unique solution in the recent context, where touching a surface by multiple people has emerged as a potential cause of infection. Traditional Biometric attendance devices are dead upgrade with contact less/Hygienic/Social distancing AI deep Learning based Facial recognition system which includes Face Detection + Mask Detection + Door Control + Attendance Management.
May write to us at info@primeinfoserv.com for further details
COM2304: Introduction to Computer Vision & Image Processing Hemantha Kulathilake
At the end of this lesson, you should be able to;
Describe image.
Describe digital image processing and computer vision.
Compare and Contrast image processing and computer vision.
Describe image sources.
Identify the array of imaging application under the EM Image source.
Describe the components of Image processing system and computer vision system.
Mika Kaukoranta presents what computer vision is and how it can be utilized in software testing by gaining high-level understanding from digital images or videos.
Lec1: Medical Image Computing - Introduction Ulaş Bağcı
2017 Spring, UCF Medical Image Computing Course
Basics of Radiological Image Modalities and their clinical use (MRI, PET, CT, fMRI, DTI, ...)
• Introduction to Medical Image Computing and Toolkits
• Image Filtering, Enhancement, Noise Reduction, and
Signal Processing
• MedicalImageRegistration
• MedicalImageSegmentation
• MedicalImageVisualization
• Machine Learning in Medical Imaging
• Shape Modeling/Analysis of Medical Images
Deep Learning in Radiology
In a world increasingly reliant on technology, the boundaries between human and machine intelligence are blurring. Google, at the forefront of this technological revolution, has revealed its latest and most ambitious project on December 6th, 2023: Gemini.
Gemini is Google's latest and most capable AI model yet, boasting state-of-the-art performance across various benchmarks. It's a multimodal model, meaning it can process and understand different information formats, including text, images, audio, and code. This makes it incredibly versatile and potentially transformative for many applications.
Gemini is based on Google's Pathways technology, which allows it to integrate multiple models into a single system. This enables it to understand and respond to complex prompts that involve different modalities.
The fear of touching public surfaces sparked by the Covid -19 outbreak is spurring a shift from fingerprint sensors to Facial Recognition Systems for allowing access to employees across offices in India.
Face recognition is a unique solution in the recent context, where touching a surface by multiple people has emerged as a potential cause of infection. Traditional Biometric attendance devices are dead upgrade with contact less/Hygienic/Social distancing AI deep Learning based Facial recognition system which includes Face Detection + Mask Detection + Door Control + Attendance Management.
May write to us at info@primeinfoserv.com for further details
COM2304: Introduction to Computer Vision & Image Processing Hemantha Kulathilake
At the end of this lesson, you should be able to;
Describe image.
Describe digital image processing and computer vision.
Compare and Contrast image processing and computer vision.
Describe image sources.
Identify the array of imaging application under the EM Image source.
Describe the components of Image processing system and computer vision system.
Mika Kaukoranta presents what computer vision is and how it can be utilized in software testing by gaining high-level understanding from digital images or videos.
Lec1: Medical Image Computing - Introduction Ulaş Bağcı
2017 Spring, UCF Medical Image Computing Course
Basics of Radiological Image Modalities and their clinical use (MRI, PET, CT, fMRI, DTI, ...)
• Introduction to Medical Image Computing and Toolkits
• Image Filtering, Enhancement, Noise Reduction, and
Signal Processing
• MedicalImageRegistration
• MedicalImageSegmentation
• MedicalImageVisualization
• Machine Learning in Medical Imaging
• Shape Modeling/Analysis of Medical Images
Deep Learning in Radiology
In a world increasingly reliant on technology, the boundaries between human and machine intelligence are blurring. Google, at the forefront of this technological revolution, has revealed its latest and most ambitious project on December 6th, 2023: Gemini.
Gemini is Google's latest and most capable AI model yet, boasting state-of-the-art performance across various benchmarks. It's a multimodal model, meaning it can process and understand different information formats, including text, images, audio, and code. This makes it incredibly versatile and potentially transformative for many applications.
Gemini is based on Google's Pathways technology, which allows it to integrate multiple models into a single system. This enables it to understand and respond to complex prompts that involve different modalities.
A Traffic Sign Classifier Model using Sage Makerijtsrd
Driver assistance technologies that relieve the drivers task, as well as intelligent autonomous vehicles, rely on traffic sign recognition. Normally the classification of traffic signs is a critical challenge for self driving cars. For the classification of traffic sign images, a Deep Network known as LeNet will be used in this study. There are forty three different categories of images in the dataset. There are two aspects to this structure Traffic sign identification and Traffic sign classification. ADASs are designed to perform a variety of tasks, including communications, detection of road markings, recognition of road signs, and detection of pedestrians. There are two aspects to this structure Traffic sign identification and Traffic sign classification. In the methodologies for detecting and recognizing traffic signals various techniques, such as colour segmentation and the RGB to HSI model area unit, were applied for traffic sign detection and recognition. Different elements contribute to recognition of HOG. Arpit Seth | Vijayakumar A "A Traffic Sign Classifier Model using Sage Maker" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42411.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42411/a-traffic-sign-classifier-model-using-sage-maker/arpit-seth
Traffic Signboard Classification with Voice alert to the driver.pptxharimaxwell0712
The basic idea of proposed system is to provide alertness to the driver about the presence of traffic signboard at a particular distance apart. It generates a warning to the driver in advance of any danger. The warning allows the driver to take appropriate actions in order to avoid the accident.The system takes continuous video input from the console monitor or camera installed on the car's bonnet. The underlying algorithm extracts the features of the input image and matches them with an existing library of traffic sign.
The output is fed to the driving assistance system and in turn drives the car accordingly. We developed this intelligent system using Machine Learning.This device will take camera feeds and upgrade the system
instantaneously.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.