Image-Based Rendering 各手法の直感的理解
•Download as PPTX, PDF•
0 likes•828 views
This document discusses several techniques for image-based rendering including light field rendering, the lumigraph, view-dependent texture mapping, the unstructured lumigraph, blending fields, and unstructured light fields. It provides intuitive explanations of each technique and how they represent scenes and allow novel views to be rendered from different positions and angles.
Report
Share
Report
Share
Recommended
Epipolarna - Project Presentation - Tracking
This document discusses object detection and tracking algorithms. It covers the following key points:
- Background modeling uses a mixture of Gaussian model to identify foreground objects from backgrounds. Tracking includes correlating current objects to previous ones and handling occlusion.
- Challenges include noisy images with false positives, shadows, and removing noise while detecting moving regions. Distance filtering and morphological operations help address these.
- Objects are identified using contours and bounding boxes. Kalman filtering can be used for prediction but has difficulties with smoothing.
- Performance is evaluated using multiple object tracking accuracy (MOTA) and multiple object tracking precision (MOTP) metrics. Areas for improvement include handling size changes and removing lost objects.
Kitchen Occupation Project Presentation
Linköping University has several student kitchens all over its campuses where students are given a possibility to warm their food. Critics claim that there are too few student kitchens and that the existing ones are usually overcrowded. That all kitchens are overcrowded at the same time has not been confirmed by sample inspections. One standing hypothesis is that students do not know where all the kitchens are, nor do they want to risk going to a kitchen in another building in case it is full as well.
The aim of this project is to develop a system that will provide the students with information regarding student kitchen usage. The system uses an computer vision approach, estimating the number of people currently using the kitchens. The system was developed using C++, the OpenCV library and the Qt5 library.
https://github.com/GroupDenseKitchen/KitchenOccupation
Lecture 4 Reconstruction from Two Views
The document summarizes lecture 4 on reconstruction from two views. It discusses techniques for shape reconstruction including shape from X methods using multiple camera views or additional information. It then covers the triangulation principle for reconstructing 3D points from 2D point correspondences in multiple views. Finally, it introduces epipolar geometry which models the geometric relationship between two views and can be used to reconstruct the fundamental matrix and epipolar lines.
Presentation Techniques - Rendered Views
The document discusses various rendering techniques in Autodesk Revit for creating high quality drawings and presentations. It covers rendering exterior and interior views, adjusting sun settings to create sunrise to night views, using photo image underlays as backgrounds, and rendering elevations and plans with different background settings like solid black. The final section provides contact information for learning more details about these rendering techniques.
Recommended
Epipolarna - Project Presentation - Tracking
This document discusses object detection and tracking algorithms. It covers the following key points:
- Background modeling uses a mixture of Gaussian model to identify foreground objects from backgrounds. Tracking includes correlating current objects to previous ones and handling occlusion.
- Challenges include noisy images with false positives, shadows, and removing noise while detecting moving regions. Distance filtering and morphological operations help address these.
- Objects are identified using contours and bounding boxes. Kalman filtering can be used for prediction but has difficulties with smoothing.
- Performance is evaluated using multiple object tracking accuracy (MOTA) and multiple object tracking precision (MOTP) metrics. Areas for improvement include handling size changes and removing lost objects.
Kitchen Occupation Project Presentation
Linköping University has several student kitchens all over its campuses where students are given a possibility to warm their food. Critics claim that there are too few student kitchens and that the existing ones are usually overcrowded. That all kitchens are overcrowded at the same time has not been confirmed by sample inspections. One standing hypothesis is that students do not know where all the kitchens are, nor do they want to risk going to a kitchen in another building in case it is full as well.
The aim of this project is to develop a system that will provide the students with information regarding student kitchen usage. The system uses an computer vision approach, estimating the number of people currently using the kitchens. The system was developed using C++, the OpenCV library and the Qt5 library.
https://github.com/GroupDenseKitchen/KitchenOccupation
Lecture 4 Reconstruction from Two Views
The document summarizes lecture 4 on reconstruction from two views. It discusses techniques for shape reconstruction including shape from X methods using multiple camera views or additional information. It then covers the triangulation principle for reconstructing 3D points from 2D point correspondences in multiple views. Finally, it introduces epipolar geometry which models the geometric relationship between two views and can be used to reconstruct the fundamental matrix and epipolar lines.
Presentation Techniques - Rendered Views
The document discusses various rendering techniques in Autodesk Revit for creating high quality drawings and presentations. It covers rendering exterior and interior views, adjusting sun settings to create sunrise to night views, using photo image underlays as backgrounds, and rendering elevations and plans with different background settings like solid black. The final section provides contact information for learning more details about these rendering techniques.
EM 3D reconstruction
This document discusses cryo-electron microscopy (cryo-EM) 3D reconstruction techniques. It describes the cryo-EM imaging process and challenges in reconstructing 3D structures from 2D projection images, including large noise and data size. The document proposes a memory-saving algorithm using tight wavelet frames for cryo-EM 3D reconstruction that formulates the reconstruction as a sparse representation problem solved with soft-thresholding and gradient descent. Simulation results on an E. coli ribosome and experimental results on an adenovirus demonstrate the proposed algorithm can reconstruct 3D structures from noisy projection data.
Meanshift Tracking Presentation
The document describes the mean shift algorithm and its application to object tracking in computer vision. Mean shift is an iterative procedure that moves data points to the average of nearby points, converging at modes of the data's probability density function. It can be used for tracking by modeling a target object's color distribution and applying mean shift to match candidate locations in subsequent frames. The algorithm maximizes the Bhattacharyya coefficient between color distributions to find the best match for the target's new location in each frame.
"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...
"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...Edge AI and Vision Alliance
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/qualcomm/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-mangen
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Michael Mangen, Product Manager for Camera and Computer Vision at Qualcomm, presents the "High-resolution 3D Reconstruction on a Mobile Processor" tutorial at the May 2016 Embedded Vision Summit.
Computer vision has come a long way. Use cases that were previously not possible in mass-market devices are now more accessible thanks to advances in depth sensors and mobile processors. In this presentation, Mangen provides an overview of how we are able to implement high-resolution 3D reconstruction – a capability typically requiring cloud/server processing – on a mobile processor. This is an exciting example of how new sensor technology and advanced mobile processors are bringing computer vision capabilities to broader markets.Kernel Bayes Rule
1) Kernel Bayes' rule provides a nonparametric approach to Bayesian inference using positive definite kernels. It represents probabilities as elements in a reproducing kernel Hilbert space.
2) Using kernel mean embeddings, kernel Bayes' rule computes the posterior kernel mean directly from covariance operators without needing to compute integrals or approximations.
3) Given samples from the joint distribution and the prior kernel mean, kernel Bayes' rule computes the posterior kernel mean as a weighted sum of prior sample kernel embeddings, providing a nonparametric realization of Bayesian inference.
3D Printing
A complete illustrated ppt on 3D printing technology. All the additive processes,Future and effects are well described with relevant diagram and images.Must download for attractive seminar presentation.3D Printing technology could revolutionize and re-shape the world. Advances in 3D printing technology can significantly change and improve the way we manufacture products and produce goods worldwide. If the last industrial revolution brought us mass production and the advent of economies of scale - the digital 3D printing revolution could bring mass manufacturing back a full circle - to an era of mass personalization, and a return to individual craftsmanship.
Raskar Computational Camera Fall 2009 Lecture 01
Keywords: Signal processing, Applied optics, Computer graphics and vision, Electronics, Art, and Online photo collections
A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes.
We will learn about the complete camera pipeline. In several hands-on projects we will build several physical imaging prototypes and understand how each stage of the imaging process can be manipulated.
We will learn about modern methods for capturing and sharing visual information. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded -- beyond those present in traditional protographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.
In this couse we will study this emerging multi-disciplinary field -- one which is at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. We will examine whether such innovative camera-like sensors can overcome the tough problems in scene understanding and generate insightful awareness. In addition, we will develop new algorithms to exploit unusual optics, programmable wavelength control, and femto-second accurate photon counting to decompose the sensed values into perceptually critical elements.
In Pursuit of Reality
By 2016, VR was the definitive tech media darling, promising the ability to not just replicate an experience, but to convince people of the validity of alternate realities. Venture funding flowed, content studios proliferated, and hardware launch dates were eagerly anticipated. Fast forward to 2017 and the equipment is still bulky and expensive, UX issues like nausea persist, and key immersive elements like haptic feedback and social interaction are still primitive. While some experiences are transformative, others underwhelm; market reports vary wildly on future investment and revenue projections.
So where exactly are we in the simulated reality hype cycle? Read the full article here: http://www.luminary-labs.com/insight/in-pursuit-of-reality/
AR - Augmented Reality
Come ogni nuova convergenza tecnologica l''Augmented Reality ridefinisce l'esperienza del corpo attraverso lo spazio e lo spazio attraverso i codici. Il buzz che circonda l'AR individua oggi un punto di convergenza tra tecnologie mature, sovraccarico delle potenzialità del presente.
44328856-Augmented-Reality.ppt
Introduction Augmented reality Augmented reality system Augmenting our ... – PowerPoint PPT presentation
44328856-Augmented-Reality.ppt
Augmented reality (AR) enhances our view of the real world by overlaying computer-generated images, audio, and other sensory enhancements. An AR system combines real and virtual objects, is interactive in real-time, and registers virtual objects in 3D. AR has applications in education, military, tourism, and gaming by providing additional information and immersive experiences overlaid on the real world. Key components of an AR system include head-mounted displays, tracking technology like GPS and compasses, and mobile computing power.
Augmented reality
This document provides an overview of augmented reality (AR) and discusses:
1. The basics of AR including scene capture, identification, processing and visualization.
2. The differences between AR and virtual reality, with AR enhancing the real world and VR being a totally immersive simulated environment.
3. Best practices of AR including providing context-sensitive information, enhancing senses, exploring the virtual in real environments, and using virtual interfaces to control real-world objects.
4. Applications of AR including navigation, military, medical, maintenance and repair, and invention.
The Extended Reality Landscape #Reality17
This is our presentation from the WebDirections #Reality17 event. It provides an overview of the Mixed/Extended Reality landscape and looks at what's coming next. It concludes by showing where #WebAR is up to right now and what's possible in your browser today.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, SerbiaModelagem de um CSTR com reação endotermica.pdf
Modelagem em função de transferencia. CSTR não-linear.
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
Bigdata of technology
More Related Content
Viewers also liked
EM 3D reconstruction
This document discusses cryo-electron microscopy (cryo-EM) 3D reconstruction techniques. It describes the cryo-EM imaging process and challenges in reconstructing 3D structures from 2D projection images, including large noise and data size. The document proposes a memory-saving algorithm using tight wavelet frames for cryo-EM 3D reconstruction that formulates the reconstruction as a sparse representation problem solved with soft-thresholding and gradient descent. Simulation results on an E. coli ribosome and experimental results on an adenovirus demonstrate the proposed algorithm can reconstruct 3D structures from noisy projection data.
Meanshift Tracking Presentation
The document describes the mean shift algorithm and its application to object tracking in computer vision. Mean shift is an iterative procedure that moves data points to the average of nearby points, converging at modes of the data's probability density function. It can be used for tracking by modeling a target object's color distribution and applying mean shift to match candidate locations in subsequent frames. The algorithm maximizes the Bhattacharyya coefficient between color distributions to find the best match for the target's new location in each frame.
"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...
"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...Edge AI and Vision Alliance
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/qualcomm/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-mangen
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Michael Mangen, Product Manager for Camera and Computer Vision at Qualcomm, presents the "High-resolution 3D Reconstruction on a Mobile Processor" tutorial at the May 2016 Embedded Vision Summit.
Computer vision has come a long way. Use cases that were previously not possible in mass-market devices are now more accessible thanks to advances in depth sensors and mobile processors. In this presentation, Mangen provides an overview of how we are able to implement high-resolution 3D reconstruction – a capability typically requiring cloud/server processing – on a mobile processor. This is an exciting example of how new sensor technology and advanced mobile processors are bringing computer vision capabilities to broader markets.Kernel Bayes Rule
1) Kernel Bayes' rule provides a nonparametric approach to Bayesian inference using positive definite kernels. It represents probabilities as elements in a reproducing kernel Hilbert space.
2) Using kernel mean embeddings, kernel Bayes' rule computes the posterior kernel mean directly from covariance operators without needing to compute integrals or approximations.
3) Given samples from the joint distribution and the prior kernel mean, kernel Bayes' rule computes the posterior kernel mean as a weighted sum of prior sample kernel embeddings, providing a nonparametric realization of Bayesian inference.
3D Printing
A complete illustrated ppt on 3D printing technology. All the additive processes,Future and effects are well described with relevant diagram and images.Must download for attractive seminar presentation.3D Printing technology could revolutionize and re-shape the world. Advances in 3D printing technology can significantly change and improve the way we manufacture products and produce goods worldwide. If the last industrial revolution brought us mass production and the advent of economies of scale - the digital 3D printing revolution could bring mass manufacturing back a full circle - to an era of mass personalization, and a return to individual craftsmanship.
Viewers also liked (8)
"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...
"High-resolution 3D Reconstruction on a Mobile Processor," a Presentation fro...
Similar to Image-Based Rendering 各手法の直感的理解
Raskar Computational Camera Fall 2009 Lecture 01
Keywords: Signal processing, Applied optics, Computer graphics and vision, Electronics, Art, and Online photo collections
A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes.
We will learn about the complete camera pipeline. In several hands-on projects we will build several physical imaging prototypes and understand how each stage of the imaging process can be manipulated.
We will learn about modern methods for capturing and sharing visual information. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded -- beyond those present in traditional protographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.
In this couse we will study this emerging multi-disciplinary field -- one which is at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. We will examine whether such innovative camera-like sensors can overcome the tough problems in scene understanding and generate insightful awareness. In addition, we will develop new algorithms to exploit unusual optics, programmable wavelength control, and femto-second accurate photon counting to decompose the sensed values into perceptually critical elements.
In Pursuit of Reality
By 2016, VR was the definitive tech media darling, promising the ability to not just replicate an experience, but to convince people of the validity of alternate realities. Venture funding flowed, content studios proliferated, and hardware launch dates were eagerly anticipated. Fast forward to 2017 and the equipment is still bulky and expensive, UX issues like nausea persist, and key immersive elements like haptic feedback and social interaction are still primitive. While some experiences are transformative, others underwhelm; market reports vary wildly on future investment and revenue projections.
So where exactly are we in the simulated reality hype cycle? Read the full article here: http://www.luminary-labs.com/insight/in-pursuit-of-reality/
AR - Augmented Reality
Come ogni nuova convergenza tecnologica l''Augmented Reality ridefinisce l'esperienza del corpo attraverso lo spazio e lo spazio attraverso i codici. Il buzz che circonda l'AR individua oggi un punto di convergenza tra tecnologie mature, sovraccarico delle potenzialità del presente.
44328856-Augmented-Reality.ppt
Introduction Augmented reality Augmented reality system Augmenting our ... – PowerPoint PPT presentation
44328856-Augmented-Reality.ppt
Augmented reality (AR) enhances our view of the real world by overlaying computer-generated images, audio, and other sensory enhancements. An AR system combines real and virtual objects, is interactive in real-time, and registers virtual objects in 3D. AR has applications in education, military, tourism, and gaming by providing additional information and immersive experiences overlaid on the real world. Key components of an AR system include head-mounted displays, tracking technology like GPS and compasses, and mobile computing power.
Augmented reality
This document provides an overview of augmented reality (AR) and discusses:
1. The basics of AR including scene capture, identification, processing and visualization.
2. The differences between AR and virtual reality, with AR enhancing the real world and VR being a totally immersive simulated environment.
3. Best practices of AR including providing context-sensitive information, enhancing senses, exploring the virtual in real environments, and using virtual interfaces to control real-world objects.
4. Applications of AR including navigation, military, medical, maintenance and repair, and invention.
The Extended Reality Landscape #Reality17
This is our presentation from the WebDirections #Reality17 event. It provides an overview of the Mixed/Extended Reality landscape and looks at what's coming next. It concludes by showing where #WebAR is up to right now and what's possible in your browser today.
Similar to Image-Based Rendering 各手法の直感的理解 (7)
Recently uploaded
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, SerbiaModelagem de um CSTR com reação endotermica.pdf
Modelagem em função de transferencia. CSTR não-linear.
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
Bigdata of technology
Low power architecture of logic gates using adiabatic techniques
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
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.
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
Kinematics 11th jpp- 01. ( Solved ) unacademy namo kaul on 14th may...
Recycled Concrete Aggregate in Construction Part III
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
DfMAy 2024 - key insights and contributions
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
New techniques for characterising damage in rock slopes.pdf
rock mass characterization and New techniques for characterising damage in rock slopes
Understanding Inductive Bias in Machine Learning
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Recently uploaded (20)
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
Low power architecture of logic gates using adiabatic techniques
Low power architecture of logic gates using adiabatic techniques
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
Recycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part III
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
New techniques for characterising damage in rock slopes.pdf
New techniques for characterising damage in rock slopes.pdf
Image-Based Rendering 各手法の直感的理解
- 1. Reality Media Lab. Image-Based Rendering 各手法の直感的理解 2014年6月19日 森 尚平
- 2. Reality Media Lab. 2 Scene Light Field Rendering u s
- 3. Reality Media Lab. 3 Scene Light Field Rendering u s
- 4. Reality Media Lab. 4 Scene Light Field Rendering u s u0 s0
- 5. Reality Media Lab. 5 Scene Light Field Rendering u s u0 s0
- 6. Reality Media Lab. 6 Scene The Lumigraph
- 7. Reality Media Lab. 7 Scene The Lumigraph u Geometry Proxy
- 8. Reality Media Lab. 8 Scene The Lumigraph u Geometry Proxy
- 9. Reality Media Lab. 9 Scene The Lumigraph u Geometry Proxy
- 10. Reality Media Lab. 10 Scene The Lumigraph u Geometry Proxy
- 11. Reality Media Lab. 11 Scene The Lumigraph u Geometry Proxy
- 12. Reality Media Lab. 12 View-Dependent Texture Mapping Scene
- 13. Reality Media Lab. 13 View-Dependent Texture Mapping Scene
- 14. Reality Media Lab. 14 View-Dependent Texture Mapping Scene
- 15. Reality Media Lab. 15 View-Dependent Texture Mapping Scene
- 16. Reality Media Lab. 16 View-Dependent Texture Mapping Scene
- 17. Reality Media Lab. 17 View-Dependent Texture Mapping Scene
- 18. Reality Media Lab. 18 View-Dependent Texture Mapping Scene Projective Texture Mapping
- 19. Reality Media Lab. 19 View-Dependent Texture Mapping Scene Projective Texture Mapping Rendering
- 20. Reality Media Lab. 20 View-Dependent Texture Mapping Scene
- 21. Reality Media Lab. 21 Unstructured Lumigraph Scene u Geometry Proxy
- 22. Reality Media Lab. 22 Unstructured Lumigraph Scene u Geometry Proxy Angle Penalty
- 23. Reality Media Lab. 23 Unstructured Lumigraph Scene u Geometry Proxy Angle Penalty Resolution Penalty
- 24. Reality Media Lab. 24 Unstructured Lumigraph Scene u Geometry Proxy Angle Penalty Field-of-View Penalty Resolution Penalty
- 25. Reality Media Lab. 25 Blending Field Scene u Geometry Proxy
- 26. Reality Media Lab. 26 Blending Field Scene u Geometry Proxy
- 27. Reality Media Lab. 27 Blending Field Scene u Geometry Proxy
- 28. Reality Media Lab. 28 Unstructured Light Fields Scene Geometry Proxy
- 29. Reality Media Lab. 29 Unstructured Light Fields Scene Geometry Proxy