Price: $29.99
(as of Dec 24,2024 10:45:02 UTC – Details)
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Price: $80.00
(as of Dec 24,2024 10:00:49 UTC – Details)
Publisher : Now Publishers (September 30, 2024)
Language : English
Paperback : 118 pages
ISBN-10 : 1638283540
ISBN-13 : 978-1638283546
Item Weight : 6.2 ounces
Dimensions : 6.14 x 0.25 x 9.21 inches
In recent years, computer vision has made significant advancements in various applications, from healthcare to autonomous vehicles. However, there is growing concern about the fairness and ethical implications of computer vision systems, particularly in areas such as bias, privacy, and discrimination.
In our latest research paper, “Beyond Fairness in Computer Vision: A Holistic Approach to Mitigating Harms and Fostering Community-Rooted Computer Vision Research,” published in Foundations and Trends(r) in Computer Graphics and Vision, we propose a comprehensive framework for addressing these challenges.
Our approach goes beyond traditional fairness metrics and focuses on creating community-rooted computer vision research that is inclusive, transparent, and accountable. We emphasize the importance of involving diverse stakeholders, including marginalized communities, in the design and evaluation of computer vision systems to ensure that they are fair and equitable.
Furthermore, we highlight the need for interdisciplinary collaboration between computer vision researchers, ethicists, policymakers, and community advocates to address the complex ethical issues surrounding computer vision technology. By taking a holistic approach, we can mitigate harms and foster a more responsible and socially conscious use of computer vision systems.
We believe that our framework provides a roadmap for advancing the field of computer vision in a way that benefits society as a whole. We invite researchers, practitioners, and policymakers to join us in this important conversation and work together to build a more ethical and inclusive future for computer vision technology.
#Fairness #Computer #Vision #Holistic #Approach #Mitigating #Harms #Fostering #CommunityRooted #Computer #Vision #Research #Foundations #Trendsr #Computer #Graphics #Vision
OV5693 5MP HD USB camera module AF/FF 73° for machine vision products
Price : 23.30
Ends on : N/A
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Introducing the OV5693 5MP HD USB camera module with AF/FF and a wide 73° field of view, perfect for machine vision products!
This high-quality camera module is equipped with advanced autofocus and fixed focus capabilities, allowing for clear and precise imaging in a variety of applications. Whether you’re developing a robotic system, industrial inspection tool, or medical device, the OV5693 is the perfect solution for capturing detailed images with ease.
With its 5MP resolution and HD video recording capabilities, this camera module delivers exceptional image quality for all your machine vision needs. The wide 73° field of view ensures that you capture a broad range of subjects in your frame, making it ideal for monitoring production lines, tracking objects, and more.
Don’t settle for subpar imaging solutions – choose the OV5693 5MP HD USB camera module for your machine vision products and experience the difference in performance and reliability. Upgrade your system today and unlock a world of possibilities with this cutting-edge camera module! #MachineVision #CameraModule #OV5693 #HDImaging
#OV5693 #5MP #USB #camera #module #AFFF #machine #vision #products,with 5mp webcam
Price: $9.99
(as of Dec 24,2024 09:08:51 UTC – Details)
From the Publisher
Daniel wrote this book for beginners in general – not only PyTorch beginners. Every now and then he will spend some time explaining some fundamental concepts which are essential to have a proper understanding of what’s going on in the code.
If your goal is to learn about deep learning models for computer vision, and you’re already comfortable training simple models in PyTorch, this volume is the right one for you.
In this second volume of the series, you’ll be introduced to deeper models and activation functions, convolutional neural networks, initialization schemes, learning rate schedulers, transfer learning, and more.
By the time you finish this book, you’ll have a thorough understanding of the concepts and tools necessary to start developing, training, and fine-tuning computer-vision models using PyTorch.
What’s inside
Deep models, activation functions, and feature spaces
Torchvision, datasets, models, and transforms
Convolutional neural networks, dropout, and learning rate schedulers
Transfer learning and fine-tuning popular models (ResNet, Inception, etc.)
… and more!
This book is written as if YOU, the reader, were having a conversation with Daniel, the author: he will ask you questions (and give you answers shortly afterward) and also make some (silly) jokes.
Moreover, this book spells concepts out in plain English, avoiding fancy mathematical notation as much as possible.
It shows you the inner workings of computer vision models, in a structured, incremental, and from-first-principles approach.
It builds, step-by-step, not only the models themselves but also your understanding as it shows you both the reasoning behind the code and how to avoid some common pitfalls and errors along the way.
I am a data scientist, developer, teacher, and author of this series of books.
I will tell you, briefly, how this series of books came to be. In 2018, before teaching a class, I tried to find a blog post that would visually explain, in a clear and concise manner, the concepts behind binary cross-entropy so that I could show it to my students. Since I could not find any that fit my purpose, I decided to write one myself. It turned out to be my most popular blog post!
My readers have welcomed the simple, straightforward, and conversational way I explained the topic.
Then, in 2019, I used the same approach for writing another blog post: “Understanding PyTorch with an example: a step-by-step tutorial.” Once again, I was amazed by the reaction from the readers! It was their positive feedback that motivated me to write this series of books to help beginners start their journey into deep learning and PyTorch.
I hope you enjoy reading these books as much as I enjoyed writing them!
ASIN : B09R152KC7
Publisher : Self-Published (January 22, 2022)
Publication date : January 22, 2022
Language : English
File size : 20353 KB
Simultaneous device usage : Unlimited
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 398 pages
In this post, we will cover the second volume of our beginner’s guide to Deep Learning with PyTorch focusing on Computer Vision.
Computer Vision is the field of study that enables computers to interpret and understand the visual world. It has a wide range of applications such as image recognition, object detection, image segmentation, and more.
In this volume, we will dive deeper into the world of Computer Vision and explore how PyTorch can be used to build powerful deep learning models for image processing tasks.
Some of the topics we will cover include:
1. Introduction to Computer Vision and its applications
2. Image preprocessing techniques such as normalization, data augmentation, and resizing
3. Building Convolutional Neural Networks (CNNs) for image classification
4. Transfer learning and fine-tuning pre-trained models for custom tasks
5. Object detection using popular architectures like YOLO and Faster R-CNN
6. Image segmentation using Fully Convolutional Networks (FCNs)
By the end of this volume, you will have a solid understanding of how to apply Deep Learning techniques to solve real-world Computer Vision problems using PyTorch. Stay tuned for more in-depth tutorials and hands-on exercises to help you master the art of Computer Vision with PyTorch.
#Deep #Learning #PyTorch #StepbyStep #Beginners #Guide #Volume #Computer #Vision
Price: $24.99
(as of Dec 24,2024 09:01:16 UTC – Details)
What are the cores? The Grove – Vision AI V2 is a highly efficient MCU-based smart vision module driven by the Himax WiseEye2 HX6538 processor, featuring a dual-core Arm Cortex-M55 and integrated Arm Ethos-U55 neural network component. It integrates Arm Helium technology, which is finely optimized for vector data processiong, enables a significant uplift in DSP and ML capabilities without compromising on power consumption, which is ideal for battery-powered applications. How’s the performance of Grove Vision AI V2? To have a quick evaluation of this board’s performance, we compared it to Seeed’s other MCU-based vision AI boards – Grove Vision AI Module, XIAO ESP32S3 Sense in four areas: 1. Power consumption: This metric indicates whether the board can be used in battery-powered products. 2. Inference time: This metric indicates the processing speed of the MCU and how much latency is involved. 3. Frame rate: This metric evaluates whether the product can capture instant changes, patterns, and movements. 4. Ease of use: We assessed whether this product is user-friendly for vision AI novices and can quickly run mainstream models on the market. What’s on the board? Grove Vision AI V2 is now compatible with all Pi cameras through a standard CSI interface. Grove Vision AI V2 is not only designed for vision applications but also features an onboard PDM microphone for sound applications. It comes with a SD card slot allows for convenient storage of images, videos, and identification results using an SD card. With various interfaces like IIC, UART, SPI, and Type-C, this board has expansive capabilities and can be easily connected to popular products such as Seeed Studio XIAO, Grove, Raspberry Pi, BeagleBoard and ESP-based products for further development. For instance, integrating Grove Vision AI V2 with XIAO can effortlessly access the interface and data of Grove Vision AI V2 through Arduino, Micropython, CircuitPython, and PlatformIO, and conveniently connect to the cloud or dedicated servers like Home Assistance.
Powerful AI Processing Capabilities: Utilizes WiseEye2 HX6538 processor with a dual-core Arm Cortex-M55 and integrated Arm Ethos-U55 neural network unit.
Versatile AI Model Support: Easily deploy off-the-shelf or your custom AI models from SenseCraft AI, including Mobilenet V1, V2, Efficientnet-lite, Yolo v5 & v8. TensorFlow and PyTorch frameworks are supported.
Rich Peripheral Devices: Includes PDM microphone, SD card slot, Type-C, Grove interface, and other peripherals.
High Compatibility: Compatible with XIAO series, Arduino, Raspberry Pi, ESP dev board, easy for further development
Fully Open Source: All codes, design files, and schematics available for modification and use.
Introducing the Grove – Vision AI Module V2, the latest innovation in artificial intelligence technology! This module features the powerful Arm Cortex-M55 processor and Ethos-U55 microNPU, providing unparalleled performance for your AI projects.
With support for TensorFlow and PyTorch, you can easily integrate machine learning algorithms into your applications. Whether you’re working on image recognition, object detection, or natural language processing, the Grove – Vision AI Module V2 has you covered.
This module is compatible with popular development boards such as Arduino, Raspberry Pi, Seeed Studio XIAO, and ESP-based dev boards, making it easy to get started with your AI projects. Plus, with Grove connectors, you can easily connect sensors and other modules for added functionality.
Don’t miss out on the opportunity to take your AI projects to the next level with the Grove – Vision AI Module V2. Get yours today and start building smarter, more efficient applications!
#Grove #Vision #Module #Arm #CortexM55 #EthosU55 #TensorFlow #PyTorch #Supported #Arduino #Raspberry #Seeed #Studio #XIAO #ESPBased #dev #Board #Compatible
Price: $89.99
(as of Dec 24,2024 08:29:50 UTC – Details)
Publisher : Cambridge Univ Pr; 1st edition (August 30, 2012)
Language : English
Hardcover : 598 pages
ISBN-10 : 1107011795
ISBN-13 : 978-1107011793
Item Weight : 3.09 pounds
Dimensions : 7 x 1.3 x 10.1 inches
Customers find the book provides clear explanations of key topics, backed up by careful formal presentation. They find it concise and logically structured, making it the best book for learning machine learning and computer vision. The book covers all necessary topics in computer vision, with applications beyond vision.
AI-generated from the text of customer reviews
Computer vision is a field of artificial intelligence that enables computers to interpret and analyze visual information from the real world. By using advanced algorithms and machine learning techniques, computer vision systems can understand images and videos, allowing them to recognize objects, detect patterns, and make decisions based on visual input.
From facial recognition technology to self-driving cars, computer vision has a wide range of applications across various industries. It revolutionizes the way we interact with technology and opens up new possibilities for automation and innovation.
Stay tuned for more updates on the latest trends and advancements in computer vision technology! #computervision #AI #technology #innovation
#Computer #Vision
Price: $89.99 – $68.08
(as of Dec 24,2024 07:44:21 UTC – Details)
Publisher : Springer; 1st ed. 2024 edition (January 3, 2024)
Language : English
Hardcover : 362 pages
ISBN-10 : 3031345061
ISBN-13 : 978-3031345067
Item Weight : 1.51 pounds
Dimensions : 6.14 x 0.81 x 9.21 inches
Computer vision is a rapidly advancing field that is revolutionizing the way we interact with and understand the world around us. One of the key techniques in computer vision is three-dimensional reconstruction, which involves creating a 3D model of an object or scene from a series of 2D images.
There are several techniques that are commonly used for three-dimensional reconstruction in computer vision. One popular method is structure from motion, which involves estimating the 3D structure of a scene by analyzing the motion of a camera as it moves through the environment. This technique is often used in applications such as 3D modeling, augmented reality, and robotics.
Another common technique for three-dimensional reconstruction is stereo vision, which involves using two or more cameras to capture multiple images of a scene from different viewpoints. By analyzing the differences in the images, a computer can determine the depth and structure of objects in the scene, allowing for the creation of a 3D model.
Finally, another technique that is often used for three-dimensional reconstruction is depth sensing, which involves using specialized sensors such as LiDAR or time-of-flight cameras to directly measure the depth of objects in a scene. This can be particularly useful for applications such as autonomous driving, where accurate depth information is critical for navigating complex environments.
Overall, three-dimensional reconstruction techniques are an essential tool in the field of computer vision, allowing for the creation of detailed 3D models from 2D images. As technology continues to advance, we can expect to see even more sophisticated and accurate techniques for three-dimensional reconstruction in the future.
#Computer #Vision #Threedimensional #Reconstruction #Techniques
Price: $54.99
(as of Dec 24,2024 07:18:19 UTC – Details)
Publisher : Packt Publishing (October 23, 2020)
Language : English
Paperback : 374 pages
ISBN-10 : 1800203586
ISBN-13 : 978-1800203587
Item Weight : 1.43 pounds
Dimensions : 9.25 x 7.52 x 0.78 inches
In this post, we will delve into the fascinating world of hands-on vision and behavior for self-driving cars using Python 3 and OpenCV 4. We will explore key concepts such as visual perception, lane detection, and object classification that are crucial for enabling autonomous vehicles to navigate safely and efficiently.
Visual perception is a critical aspect of self-driving cars, as they rely on cameras and sensors to interpret their surroundings and make decisions in real time. By leveraging the power of computer vision libraries such as OpenCV, we can process and analyze visual data to identify lane markings, detect obstacles, and classify objects on the road.
Lane detection is a fundamental task in autonomous driving, as it allows vehicles to stay within their designated lanes and navigate smoothly. Using techniques such as edge detection, image thresholding, and Hough transforms, we can accurately detect and track lane markings in real-world scenarios.
Object classification is another crucial component of self-driving cars, as they must be able to recognize and differentiate between various objects on the road, such as vehicles, pedestrians, and traffic signs. By training machine learning models on labeled datasets, we can develop robust object classification algorithms that can accurately identify and categorize objects in real time.
By combining visual perception, lane detection, and object classification techniques in Python 3 with OpenCV 4, we can build a comprehensive framework for enabling self-driving cars to navigate complex environments with confidence and precision. Join us on this exciting journey as we explore the cutting-edge technologies that are shaping the future of autonomous driving.
#HandsOn #Vision #Behavior #SelfDriving #Cars #Explore #visual #perception #lane #detection #object #classification #Python #OpenCV
Price: $60.99
(as of Dec 24,2024 06:59:43 UTC – Details)
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5MP USB camera high definition 2595×1944 resolution 30fps webcam board ensure your videos and image are always sharp and crystal clear with vivid color.
Dual Digital Audio, external microphones with wires for audio video recording makes this camera are perfect for machine vision, DIY and industrial.
USB Camera with 1/2.8” IMX335 CMOS Sensor, good performance in low-light environment, fine shooting images with high sensitivity, low noise. Picture format support MJPEG and YUY2.
Wide angle camera with M12 mount Fisheye lens, capture super wide angle of 200 degree viewing
Camera board with USB2.0 port, uvc plug and play for computer,raspberry pi. No extra driver or software required. Compatible for Windows,Linux,MacOS,Android.
38x38mm/32x32mm small size for embedded applications. Great for all kinds of machine vision,lightburn,laser engraver camera,dash cam
Are you looking for a high-quality USB camera module for your computer or Raspberry Pi project? Look no further than the SVPRO 5MP USB Camera Module with Microphone. This camera module features an ultra-wide angle 200-degree fisheye lens, making it perfect for industrial machine vision applications.
Whether you’re looking to add a camera to your computer for video conferencing or surveillance, or you need a reliable camera module for your Raspberry Pi project, the SVPRO 5MP USB Camera Module is a great choice. With its high resolution and microphone for audio input, this camera module is perfect for a wide range of applications.
Don’t settle for subpar camera modules – choose the SVPRO 5MP USB Camera Module for crisp, clear images and reliable performance. Order yours today and take your computer or Raspberry Pi project to the next level!
#SVPRO #5MP #USB #Camera #Module #Microphone #ComputerUltra #Wide #Angle #Degree #Fisheye #USB #Industrial #Machine #Vision #Camera #ComputerRaspberry,with 5mp webcam
Price: $59.99 – $47.99
(as of Dec 24,2024 06:56:35 UTC – Details)
Publisher : Chapman and Hall/CRC; 1st edition (October 4, 2024)
Language : English
Paperback : 438 pages
ISBN-10 : 0367755289
ISBN-13 : 978-0367755287
Item Weight : 1.34 pounds
Dimensions : 6.14 x 0.89 x 9.21 inches
Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence (Chapman & Hall/CRC Computer Vision)
Are you interested in maximizing the efficiency of your artificial intelligence systems while minimizing power consumption? Look no further than the groundbreaking new book, “Low-Power Computer Vision” from Chapman & Hall/CRC Computer Vision.
In this comprehensive guide, leading experts in the field explore the latest techniques and technologies for optimizing the performance of computer vision systems on low-power platforms. From energy-efficient algorithms to hardware design considerations, this book covers everything you need to know to make your AI systems run faster and more efficiently than ever before.
Whether you’re a researcher, developer, or industry professional, “Low-Power Computer Vision” is essential reading for anyone looking to stay ahead of the curve in the rapidly evolving field of artificial intelligence. Don’t miss out on this invaluable resource – order your copy today!
#LowPower #Computer #Vision #Improve #Efficiency #Artificial #Intelligence #Chapman #HallCRC #Computer #Vision
