Convolutional Neural Networks cnn pre.pptx
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Convolutional Neural Networks
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The document discusses anomaly detection in surveillance videos. It aims to identify anomalies to improve public safety monitoring. It reviews recent research using methods like 3D convolutional neural networks and sparse LSTM. It details 4 models tested - CNN-LSTM, ConvLSTM, VGG-16 LSTM, and Conv3D. Testing on 376 videos achieved a maximum accuracy of 54.19% for anomaly prediction using ConvLSTM. While progress was made, the authors believe accuracy could be improved by changing the model architecture, using more complete video data, and exploring other video sampling methods.
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Kd3517551759
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.
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Deepfake detection is a critical and evolving field aimed at identifying and mitigating the risks associated with manipulated multimedia content created using artificial intelligence (AI) techniques. Deepfakes involve the use of advanced machine learning algorithms, particularly generative models like Generative Adversarial Networks (GANs), to create highly convincing fake videos, audio recordings, or images that can deceive viewers into believing they are genuine.
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Deepfake detection is a critical and evolving field aimed at identifying and mitigating the risks associated with manipulated multimedia content created using artificial intelligence (AI) techniques. Deepfakes involve the use of advanced machine learning algorithms, particularly generative models like Generative Adversarial Networks (GANs), to create highly convincing fake videos, audio recordings, or images that can deceive viewers into believing they are genuine.
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1) The document discusses approaches for semantic concept detection in videos using techniques like support vector machines (SVM) and convolutional neural networks (CNN).
2) It proposes a concept detection system that uses SVM and CNN together, extracting features from key frames using Hue moments and classifying the features with SVM and CNN.
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• They are relatively expensive to produce compared to other battery technologies.
• They have a limited lifespan, typically around 2-3 years, and their capacity gradually decreases over time.
• Lithium-ion batteries can be sensitive to high temperatures and overcharging, which can cause them to overheat, swell, or catch fire.
• They require special care and handling to prevent damage, such as avoiding deep discharge and extreme temperatures.
• The production of lithium-ion batteries relies on the mining and processing of materials such as lithium, cobalt, and nickel, which can have significant environmental impacts.
• Recycling of lithium-ion batteries can be challenging and costly, leading to concerns about e-waste and sustainability.
• They are relatively expensive to produce compared to other battery technologies.
• They have a limited lifespan, typically around 2-3 years, and their capacity gradually decreases over time.
• Lithium-ion batteries can be sensitive to high temperatures and overcharging, which can cause them to overheat, swell, or catch fire.
• They require special care and handling to prevent damage, such as avoiding deep discharge and extreme temperatures.
• The production of lithium-ion batteries relies on the mining and processing of materials such as lithium, cobalt, and nickel, which can have significant environmental impacts.
• Recycling of lithium-ion batteries can be challenging and costly, leading to concerns about e-waste and sustainability.
• They are relatively expensive to produce compared to other battery technologies.
• They have a limited lifespan, typically around 2-3 years, and their capacity gradually decreases over time.
• Lithium-ion batteries can be sensitive to high temperatures and overcharging, which can cause them to overheat, swell, or catch fire.
• They require special care and handling to prevent damage, such as avoiding deep discharge and extreme temperatures.
• The production of lithium-ion batteries relies on the mining and processing of materials such as lithium, cobalt, and nickel, which can have significant environmental impacts.
• Recycling of lithium-ion batteries can be challenging and costly, leading to concerns about e-waste and sustainability.
Inspection of Suspicious Human Activity in the Crowd Sourced Areas Captured i...
The document proposes a system to detect suspicious human activity in crowdsourced video captured by surveillance cameras. The system uses Advanced Motion Detection (AMD) to detect moving objects and generate a reliable background model for analysis. A camera connected to a monitoring room would produce alert messages for any detected suspicious activity based on height, time, and body movement constraints. The system aims to automate real-time video processing for security applications like detecting unauthorized access. It extracts human objects from frames and identifies suspicious behavior using the AMD algorithm before sending alerts.
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3D perception is crucial for understanding the real world. It offers many benefits and new capabilities over 2D across diverse applications, from XR and autonomous driving to IOT, camera, and mobile. 3D perception with machine learning is creating the new state of the art (SOTA) in areas, such as depth estimation, object detection, and neural scene representation. Making these SOTA neural networks feasible for real-world deployment on mobile devices constrained by power, thermal, and performance has been a challenge. Qualcomm AI Research has developed not only novel AI techniques for 3D perception but also full-stack AI optimizations to enable real-world deployments and energy-efficient solutions. This presentation explores the latest research that is enabling efficient 3D perception while maintaining neural network model accuracy. You’ll learn about:
- The advantages of 3D perception over 2D and the need for 3D perception across applications
- Advancements in 3D perception research by Qualcomm AI Research
- Our future 3D perception research directions
A Deep Learning algorithm for automatic detection of unexpected accidents und...
The project will introduce and apply the Object Detection and Tracking System(ODTS) along with the well_known faster RCNN.
Recognition and tracking moving objects using moving camera in complex scenes
1) The document proposes a method for tracking moving objects in videos captured using a moving camera in complex scenes. It involves video stabilization, key frame extraction, object detection/tracking using Gaussian mixture models and Kalman filters, and object recognition using bag of features.
2) Key frame extraction identifies important frames for processing by computing edge differences between frames and selecting frames above a threshold.
3) Moving objects are detected using background subtraction and Gaussian mixture models, and then tracked across frames using Kalman filters.
4) Object recognition is performed using bag of features, which represents objects as histograms of visual word frequencies to classify objects based on characteristic visual parts.
Weapon Detection Using AI and DL.pptx
Weapon Detection using Machine Learning and Deep
Learning.
Technologies Used: SSD Algorithm, Faster RCNN, YOLO Algorithm. •
● Automatic weapon detection using a Convolution Neural
Network (CNN) based SSD and Faster RCNN algorithms.
● The primary goal of this project is to enhance security and
public safety.
● The process of detecting weapons in real-time or through the
analysis of recorded data, such as video feeds or images
PROJECT REPORT
This project aims to prevent fraud by checking if a user's image already exists in a bank's database when they apply for a loan. The model detects faces from images, extracts features, and uses dHash and SSIM algorithms to check for similarities between images. The output notifies the bank manager if fraud is detected by displaying matching images and customer details. The model achieves 61% accuracy but performs poorly on low-quality images or images where the user is not facing the camera. Python, OpenCV, Spark, Bottle and Java were used to build and integrate the model.
An Approach for Object and Scene Detection for Blind Peoples Using Vocal Vision.
This system help the blind peoples for the navigation without the help of third person so blind person can perform its work independently. This system implemented on android device in which object detection and scene detection implemented, so after detection there will be text to speech conversion so user or blind person can get message from that android device with the help of headphone connected to that device. Our project will help blind people to understand the images which will be converted to sound with the help of webcam. We shall capture images in front of blind peoples .The captured image will be processed through our algorithms which will enhances the image data. The hardware component will have its own database. The processed image is compare with the database in the hardware component .The result after processing and comparing will be converted into speech signals. The headphones guide the blind peoples.
Convolution Neural Network (CNN)
The presentation is made on CNN's which is explained using the image classification problem, the presentation was prepared in perspective of understanding computer vision and its applications. I tried to explain the CNN in the most simple way possible as for my understanding. This presentation helps the beginners of CNN to have a brief idea about the architecture and different layers in the architecture of CNN with the example. Please do refer the references in the last slide for a better idea on working of CNN. In this presentation, I have also discussed the different types of CNN(not all) and the applications of Computer Vision.
Supermarket Management System Project Report.pdf
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
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• They are relatively expensive to produce compared to other battery technologies.
• They have a limited lifespan, typically around 2-3 years, and their capacity gradually decreases over time.
• Lithium-ion batteries can be sensitive to high temperatures and overcharging, which can cause them to overheat, swell, or catch fire.
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Understanding the world in 3D with AI.pdf
3D perception is crucial for understanding the real world. It offers many benefits and new capabilities over 2D across diverse applications, from XR and autonomous driving to IOT, camera, and mobile. 3D perception with machine learning is creating the new state of the art (SOTA) in areas, such as depth estimation, object detection, and neural scene representation. Making these SOTA neural networks feasible for real-world deployment on mobile devices constrained by power, thermal, and performance has been a challenge. Qualcomm AI Research has developed not only novel AI techniques for 3D perception but also full-stack AI optimizations to enable real-world deployments and energy-efficient solutions. This presentation explores the latest research that is enabling efficient 3D perception while maintaining neural network model accuracy. You’ll learn about:
- The advantages of 3D perception over 2D and the need for 3D perception across applications
- Advancements in 3D perception research by Qualcomm AI Research
- Our future 3D perception research directions
A Deep Learning algorithm for automatic detection of unexpected accidents und...
The project will introduce and apply the Object Detection and Tracking System(ODTS) along with the well_known faster RCNN.
Recognition and tracking moving objects using moving camera in complex scenes
1) The document proposes a method for tracking moving objects in videos captured using a moving camera in complex scenes. It involves video stabilization, key frame extraction, object detection/tracking using Gaussian mixture models and Kalman filters, and object recognition using bag of features.
2) Key frame extraction identifies important frames for processing by computing edge differences between frames and selecting frames above a threshold.
3) Moving objects are detected using background subtraction and Gaussian mixture models, and then tracked across frames using Kalman filters.
4) Object recognition is performed using bag of features, which represents objects as histograms of visual word frequencies to classify objects based on characteristic visual parts.
Weapon Detection Using AI and DL.pptx
Weapon Detection using Machine Learning and Deep
Learning.
Technologies Used: SSD Algorithm, Faster RCNN, YOLO Algorithm. •
● Automatic weapon detection using a Convolution Neural
Network (CNN) based SSD and Faster RCNN algorithms.
● The primary goal of this project is to enhance security and
public safety.
● The process of detecting weapons in real-time or through the
analysis of recorded data, such as video feeds or images
PROJECT REPORT
This project aims to prevent fraud by checking if a user's image already exists in a bank's database when they apply for a loan. The model detects faces from images, extracts features, and uses dHash and SSIM algorithms to check for similarities between images. The output notifies the bank manager if fraud is detected by displaying matching images and customer details. The model achieves 61% accuracy but performs poorly on low-quality images or images where the user is not facing the camera. Python, OpenCV, Spark, Bottle and Java were used to build and integrate the model.
An Approach for Object and Scene Detection for Blind Peoples Using Vocal Vision.
This system help the blind peoples for the navigation without the help of third person so blind person can perform its work independently. This system implemented on android device in which object detection and scene detection implemented, so after detection there will be text to speech conversion so user or blind person can get message from that android device with the help of headphone connected to that device. Our project will help blind people to understand the images which will be converted to sound with the help of webcam. We shall capture images in front of blind peoples .The captured image will be processed through our algorithms which will enhances the image data. The hardware component will have its own database. The processed image is compare with the database in the hardware component .The result after processing and comparing will be converted into speech signals. The headphones guide the blind peoples.
Convolution Neural Network (CNN)
The presentation is made on CNN's which is explained using the image classification problem, the presentation was prepared in perspective of understanding computer vision and its applications. I tried to explain the CNN in the most simple way possible as for my understanding. This presentation helps the beginners of CNN to have a brief idea about the architecture and different layers in the architecture of CNN with the example. Please do refer the references in the last slide for a better idea on working of CNN. In this presentation, I have also discussed the different types of CNN(not all) and the applications of Computer Vision.
Similar to Convolutional Neural Networks cnn pre.pptx (20)
Design and Analysis of Quantization Based Low Bit Rate Encoding System
Design and Analysis of Quantization Based Low Bit Rate Encoding System
VIDEO BASED SIGN LANGUAGE RECOGNITION USING CNN-LSTM
VIDEO BASED SIGN LANGUAGE RECOGNITION USING CNN-LSTM
Transfer Learning and Fine-tuning Deep Neural Networks
Transfer Learning and Fine-tuning Deep Neural Networks
IRJET- Study of SVM and CNN in Semantic Concept Detection
IRJET- Study of SVM and CNN in Semantic Concept Detection
Inspection of Suspicious Human Activity in the Crowd Sourced Areas Captured i...
Inspection of Suspicious Human Activity in the Crowd Sourced Areas Captured i...
A Deep Learning algorithm for automatic detection of unexpected accidents und...
A Deep Learning algorithm for automatic detection of unexpected accidents und...
Recognition and tracking moving objects using moving camera in complex scenes
Recognition and tracking moving objects using moving camera in complex scenes
An Approach for Object and Scene Detection for Blind Peoples Using Vocal Vision.
An Approach for Object and Scene Detection for Blind Peoples Using Vocal Vision.
Recently uploaded
Supermarket Management System Project Report.pdf
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
Impartiality as per ISO /IEC 17025:2017 Standard
This document provides basic guidelines for imparitallity requirement of ISO 17025. It defines in detial how it is met and wiudhwdih jdhsjdhwudjwkdbjwkdddddddddddkkkkkkkkkkkkkkkkkkkkkkkwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwioiiiiiiiiiiiii uwwwwwwwwwwwwwwwwhe wiqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq gbbbbbbbbbbbbb owdjjjjjjjjjjjjjjjjjjjj widhi owqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq uwdhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhwqiiiiiiiiiiiiiiiiiiiiiiiiiiiiw0pooooojjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj whhhhhhhhhhh wheeeeeeee wihieiiiiii wihe
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Applications of artificial Intelligence in Mechanical Engineering.pdf
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
FULL STACK PROGRAMMING - Both Front End and Back End
This ppt gives details about Full Stack Programming and its basics.
Flow Through Pipe: the analysis of fluid flow within pipes
Flow Through Pipe: This topic covers the analysis of fluid flow within pipes, focusing on laminar and turbulent flow regimes, continuity equation, Bernoulli's equation, Darcy-Weisbach equation, head loss due to friction, and minor losses from fittings and bends. Understanding these principles is crucial for efficient pipe system design and analysis.
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Object Oriented Analysis and Design - OOAD
This ppt gives detailed description of Object Oriented Analysis and design.
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
* Registration is currently open *
Call for Research Papers!!!
Free – Extended Paper will be published as free of cost.
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
July 13 ~ 14, 2024, Virtual Conference
Webpage URL: https://aiad2024.org/index
Submission Deadline: June 22, 2024
Submission System URL:
https://aiad2024.org/submission/index.php
Contact Us:
Here's where you can reach us : aiad@aiad2024.org (or) aiadconference@yahoo.com
WikiCFP URL: http://wikicfp.com/cfp/servlet/event.showcfp?eventid=180509©ownerid=171656
#artificialintelligence #softcomputing #machinelearning #technology #datascience #python #deeplearning #tech #robotics #innovation #bigdata #coding #iot #computerscience #data #dataanalytics #engineering #robot #datascientist #software #automation #analytics #ml #pythonprogramming #programmer #digitaltransformation #developer #promptengineering #generativeai #genai #chatgpt #artificial #intelligence #datamining #networkscommunications #robotics #callforsubmission #submissionsopen #deadline #opencall #virtual #conference
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...Paris Salesforce Developer Group
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.OOPS_Lab_Manual - programs using C++ programming language
This manual contains programs on object oriented programming concepts using C++ language.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
Determination of Equivalent Circuit parameters and performance characteristic...
Includes the testing of induction motor to draw the circle diagram of induction motor with step wise procedure and calculation for the same. Also explains the working and application of Induction generator
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
3rd International Conference on Artificial Intelligence Advances (AIAD 2024) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Artificial Intelligence. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the research area. Core areas of AI and advanced multi-disciplinary and its applications will be covered during the conferences.
Recently uploaded (20)
Applications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdf
FULL STACK PROGRAMMING - Both Front End and Back End
FULL STACK PROGRAMMING - Both Front End and Back End
Flow Through Pipe: the analysis of fluid flow within pipes
Flow Through Pipe: the analysis of fluid flow within pipes
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Northrop Grumman - Aerospace Structures Overvi.pdf
Northrop Grumman - Aerospace Structures Overvi.pdf
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
OOPS_Lab_Manual - programs using C++ programming language
OOPS_Lab_Manual - programs using C++ programming language
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...
Determination of Equivalent Circuit parameters and performance characteristic...
Determination of Equivalent Circuit parameters and performance characteristic...
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
Convolutional Neural Networks cnn pre.pptx
- 2. Introduction In this work, we propose the use of an existing pre-trained 3D Convolutional Neural Network (CNN), named C3D . Here we use CNN for violence detection in videos through cameras and going to implement next move to protect us .
- 3. 3D CNN can understand the movement over time in videos. It does this by using 3D convolution and pooling. This means it looks at groups of frames stacked together to figure out how things change over time 3D CNN :
- 4. Figure of Convolution and pooling Figure of frame detection in videos
- 5. VIOLENCE DETECTION : Detecting violence in video data presents a significant challenge due to the intricate identification of complex sequential visual patterns. There are many unimportant frames so it takes more memory .so , we first detected the persons in the video stream using a pre-trained CNN model. Only the sequence of 16 frames containing persons was passed to the 3D CNN model for final prediction, which helped achieve effiecient processing.
- 6. ABNORMAL ACTIVITY: NORMAL ACTIVITY:
- 7. OUR IDEA OF IMPLEMENTATION : It is impossible to detect every violence through cctv camers Accurately. By implementing our idea through cam specs we can able detect every video frames accurately using 3D CNN. And it’s easy to protect us from major threads like harassment And informal attacks. Hope ,Even it works better than Kavalan SOS which is implemented by our TN government