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Tag: computer vision
Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition)
Price: $88.00
(as of Dec 24,2024 17:13:03 UTC – Details)
Computer vision is an exciting field that is constantly evolving with new advancements in technology. One of the most cutting-edge techniques in computer vision is deep learning, a subset of machine learning that uses neural networks to analyze and interpret visual data.Advanced methods in computer vision, such as deep learning, have revolutionized the way we approach image and video analysis. These methods have allowed for more accurate object recognition, image segmentation, and scene understanding.
Deep learning algorithms are able to learn complex patterns and features from large amounts of visual data, making them highly effective in tasks such as image classification, object detection, and image generation.
In the field of computer vision and pattern recognition, researchers are constantly exploring new ways to improve the performance of deep learning models. Techniques such as transfer learning, data augmentation, and adversarial training are being used to enhance the capabilities of deep learning algorithms.
Advancements in computer vision are being applied to a wide range of industries, including healthcare, automotive, and security. From medical image analysis to autonomous vehicles, deep learning in computer vision is revolutionizing the way we interact with visual data.
As researchers continue to push the boundaries of computer vision technology, we can expect to see even more exciting advancements in the field. The future of computer vision is bright, and deep learning is paving the way for more intelligent and efficient visual analysis.
#Advanced #Methods #Deep #Learning #Computer #Vision #Computer #Vision #Pattern #Recognition
Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition
Price: $17.97
(as of Dec 24,2024 16:33:02 UTC – Details)
ASIN : B085P1HWPM
Publisher : Packt Publishing; 2nd edition (June 29, 2020)
Publication date : June 29, 2020
Language : English
File size : 25796 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 306 pages
If you’re looking to dive into the world of computer vision programming using Raspberry Pi, OpenCV, and Python 3, then the newly released 2nd edition of “Raspberry Pi Computer Vision Programming” is the perfect guide for you.This comprehensive book covers everything you need to know to design and implement computer vision applications on the popular Raspberry Pi platform. From setting up your Raspberry Pi and installing OpenCV to creating your own image processing and object detection programs, this book walks you through the entire process step by step.
With practical examples and hands-on projects, you’ll learn how to harness the power of Raspberry Pi and OpenCV to build real-world computer vision applications. Whether you’re a beginner looking to get started with computer vision programming or a seasoned developer looking to expand your skills, this book has something for everyone.
So grab your Raspberry Pi, fire up your Python interpreter, and get ready to unlock the full potential of computer vision programming with “Raspberry Pi Computer Vision Programming, 2nd Edition”.
#Raspberry #Computer #Vision #Programming #Design #implement #computer #vision #applications #Raspberry #OpenCV #Python #2nd #Edition
Building Computer Vision Projects with OpenCV 4 and C++
Price:$49.99– $47.42
(as of Dec 24,2024 15:49:39 UTC – Details)
Publisher : Packt Publishing (March 22, 2019)
Language : English
Paperback : 538 pages
ISBN-10 : 1838644679
ISBN-13 : 978-1838644673
Item Weight : 2.05 pounds
Dimensions : 9.25 x 7.5 x 1.11 inches
Building Computer Vision Projects with OpenCV 4 and C++Are you interested in diving into the world of computer vision and creating projects using OpenCV 4 and C++? Look no further! In this post, we will explore how you can start building your own computer vision projects using the powerful combination of OpenCV 4 and C++.
OpenCV 4 is a popular open-source computer vision and machine learning software library that provides tools and algorithms for image and video processing. With the recent release of OpenCV 4, developers have access to even more features and improvements for their computer vision projects.
To get started with building computer vision projects using OpenCV 4 and C++, you will need to have a basic understanding of C++ programming and some knowledge of computer vision concepts. If you are new to C++ or computer vision, there are plenty of resources available online to help you get up to speed.
Once you have a good grasp of C++ and computer vision fundamentals, you can begin exploring the various functionalities of OpenCV 4. Some popular projects that you can build using OpenCV 4 and C++ include object detection, facial recognition, image segmentation, and more.
To start building your own computer vision project, you can download and install OpenCV 4 from the official website and set up your development environment. You can then begin writing C++ code to implement the desired functionality, using the OpenCV 4 library functions and algorithms.
Overall, building computer vision projects with OpenCV 4 and C++ can be a rewarding and exciting experience. With the powerful tools and capabilities of OpenCV 4, you can create sophisticated computer vision applications that can analyze and process images and videos in real-time. So why wait? Start exploring the world of computer vision today with OpenCV 4 and C++!
#Building #Computer #Vision #Projects #OpenCV
Mastering Computer Vision with PyTorch and Machine Learning
Price:$120.00– $90.39
(as of Dec 24,2024 15:07:28 UTC – Details)
Publisher : Iop Publishing Ltd (September 20, 2024)
Language : English
Hardcover : 364 pages
ISBN-10 : 0750362421
ISBN-13 : 978-0750362429
Item Weight : 1.87 pounds
Dimensions : 7.35 x 1 x 10.3 inches
Are you ready to take your computer vision skills to the next level? Join us for an intensive workshop on mastering computer vision with PyTorch and machine learning. In this hands-on session, you will learn how to build and train deep learning models for image recognition, object detection, and more using the powerful PyTorch framework.Our expert instructors will guide you through the fundamentals of computer vision, including image preprocessing, data augmentation, and model evaluation. You will also have the opportunity to work on real-world projects and gain practical experience in applying computer vision techniques to solve complex problems.
Whether you are a seasoned machine learning practitioner or a beginner looking to dive into the world of computer vision, this workshop is perfect for anyone who wants to enhance their skills and stay ahead in this rapidly evolving field. Don’t miss out on this opportunity to become a master of computer vision with PyTorch and machine learning. Sign up now and take your career to new heights!
#Mastering #Computer #Vision #PyTorch #Machine #Learning
Hands-On Computer Vision with Detectron2: Develop object detection and segmentation models with a code and visualization approach
Price: $43.13
(as of Dec 24,2024 14:26:14 UTC – Details)
Hands-On Computer Vision with Detectron2: Develop object detection and segmentation models with a code and visualization approachIn this post, we will explore how to build advanced computer vision models using Detectron2, a powerful open-source framework for object detection and segmentation developed by Facebook AI Research. With Detectron2, you can easily train and deploy state-of-the-art models for a wide range of computer vision tasks.
To get started, we will walk you through the process of setting up Detectron2 and training your own object detection and segmentation models. We will provide code snippets and visualization techniques to help you understand the inner workings of the models and optimize their performance.
By the end of this post, you will have a solid understanding of how to use Detectron2 to develop cutting-edge computer vision applications. So, grab your favorite IDE and let’s dive into the exciting world of computer vision with Detectron2!
#HandsOn #Computer #Vision #Detectron2 #Develop #object #detection #segmentation #models #code #visualization #approach
Computer Vision and Image Processing: Fundamentals and Applications
Price:$170.00– $128.52
(as of Dec 24,2024 13:42:58 UTC – Details)
Computer Vision and Image Processing: Fundamentals and ApplicationsComputer vision and image processing are two closely related fields that have revolutionized the way we interact with technology. From facial recognition on our smartphones to autonomous vehicles, these technologies have a wide range of applications in various industries.
Computer vision is the field of study that focuses on enabling computers to interpret and understand visual information from the real world. This involves tasks such as object detection, image classification, and image segmentation. Image processing, on the other hand, involves manipulating and enhancing visual images to improve their quality or extract useful information.
Fundamentally, computer vision and image processing rely on algorithms and techniques that analyze and interpret visual data. This includes machine learning algorithms, neural networks, and deep learning techniques. By training these models on large datasets, computers can learn to recognize patterns and make decisions based on visual information.
The applications of computer vision and image processing are vast and diverse. In the medical field, these technologies are used for diagnosing diseases from medical images, such as X-rays and MRIs. In the automotive industry, computer vision is crucial for enabling autonomous vehicles to navigate and detect obstacles on the road. In retail, these technologies are used for facial recognition and tracking customer behavior in stores.
Overall, computer vision and image processing have transformed the way we interact with technology and have enabled a wide range of innovative applications. As these fields continue to advance, we can expect to see even more groundbreaking developments in the future.
#Computer #Vision #Image #Processing #Fundamentals #Applications
Learning OpenCV 4 Computer Vision with Python 3
Price:$49.99– $37.48
(as of Dec 24,2024 12:59:34 UTC – Details)
Publisher : Packt Publishing; 3rd ed. edition (February 20, 2020)
Language : English
Paperback : 372 pages
ISBN-10 : 1789531616
ISBN-13 : 978-1789531619
Item Weight : 1.43 pounds
Dimensions : 9.25 x 7.5 x 0.78 inchesCustomers say
Customers find the book well-written and readable. They describe it as an engaging introduction to OpenCV that provides clear explanations of the basics. However, some readers feel the lessons are unclear or lack certain details.
AI-generated from the text of customer reviews
Introduction to OpenCV 4 Computer Vision with Python 3
OpenCV (Open Source Computer Vision Library) is a powerful open-source computer vision and machine learning software library. It is widely used in various applications such as image and video processing, object detection, facial recognition, and more.
In this post, we will explore the basics of learning OpenCV 4 computer vision with Python 3. Python is a popular programming language for computer vision tasks due to its simplicity and rich ecosystem of libraries.
To get started with OpenCV 4 and Python 3, you will need to install the OpenCV library on your machine. You can easily install OpenCV using pip, a package manager for Python. Simply run the following command in your terminal:
pip install opencv-python<br /> ```<br /> <br /> Once you have installed OpenCV, you can start writing Python scripts to perform various computer vision tasks. Some common tasks that you can perform with OpenCV include:<br /> <br /> 1. Loading and displaying images: You can use OpenCV to load images from files and display them on your screen.<br /> 2. Image processing: OpenCV provides a wide range of image processing functions such as blurring, sharpening, and edge detection.<br /> 3. Object detection: OpenCV includes pre-trained models for object detection tasks, such as detecting faces, pedestrians, and vehicles.<br /> 4. Feature detection: OpenCV can be used to detect and extract features from images, such as corners, edges, and blobs.<br /> 5. Video processing: OpenCV supports video processing tasks, such as capturing video from a camera, reading video files, and processing video frames.<br /> <br /> In the upcoming posts, we will delve deeper into each of these topics and explore more advanced computer vision techniques using OpenCV and Python. Stay tuned for more tutorials and practical examples on how to leverage the power of OpenCV for your computer vision projects.<br /> <br /> Happy coding!#Learning #OpenCV #Computer #Vision #Python
Computer Vision: Algorithms and Applications (Texts in Computer Science)
Price: $121.79
(as of Dec 24,2024 12:15:16 UTC – Details)
Publisher : Springer; 2011th edition (October 19, 2010)
Language : English
Hardcover : 832 pages
ISBN-10 : 1848829345
ISBN-13 : 978-1848829343
Item Weight : 6.91 pounds
Dimensions : 8.9 x 1.5 x 11.3 inchesCustomers say
Customers find the book provides a good introduction to computer vision with clear explanations and insights. It includes plenty of diagrams and color photos. The writing quality is described as well-written and easy to read like a storybook. Many customers consider it reasonably priced and say it has already paid for itself in time savings. However, some readers feel the book attempts to cover too much information and doesn’t always go very deep. There are mixed opinions on the introduction, with some finding it comprehensive and providing a wide summary of introductory concepts, while others feel it lacks depth and explanations in sufficient detail.
AI-generated from the text of customer reviews
Computer Vision: Algorithms and Applications (Texts in Computer Science)Computer vision is a rapidly expanding field that has revolutionized the way we interact with technology. From facial recognition to autonomous vehicles, computer vision algorithms are at the core of many cutting-edge applications.
In the book “Computer Vision: Algorithms and Applications,” readers will delve into the fundamental principles and advanced techniques of computer vision. Written by experts in the field, this comprehensive text covers topics such as image formation, image processing, feature detection, object recognition, and more.
Whether you are a student studying computer science or a professional looking to enhance your knowledge of computer vision, this book provides a solid foundation for understanding the theory and practical applications of this exciting field.
With real-world examples and hands-on exercises, “Computer Vision: Algorithms and Applications” is a valuable resource for anyone interested in exploring the possibilities of computer vision technology.
#Computer #Vision #Algorithms #Applications #Texts #Computer #Science
The Birth of Computer Vision
Price: $15.66
(as of Dec 24,2024 11:31:49 UTC – Details)
ASIN : B0BHKH7T68
Publisher : Univ Of Minnesota Press (April 4, 2023)
Publication date : April 4, 2023
Language : English
File size : 2699 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Enabled
Print length : 214 pages
The Birth of Computer VisionComputer vision, the field of computer science that enables computers to interpret and understand visual information from the world, has come a long way since its inception. It all started in the 1960s, when researchers began exploring the idea of teaching computers to see and interpret images like humans do.
One of the earliest breakthroughs in computer vision came in 1966, when MIT professor Seymour Papert and graduate student Marvin Minsky created the first computer program that could identify objects in simple black and white images. This program, known as the “Summer Vision Project,” paved the way for further advancements in the field.
Over the years, computer vision has evolved drastically, thanks to advancements in artificial intelligence, machine learning, and deep learning. Today, computer vision is used in a wide range of applications, from facial recognition and autonomous vehicles to medical imaging and augmented reality.
As technology continues to advance, the future of computer vision looks brighter than ever. With the ability to analyze and understand visual data at scale, computers are now able to perceive the world in ways that were once only possible for humans. The birth of computer vision has revolutionized the way we interact with technology and has opened up a world of new possibilities for innovation and discovery.
#Birth #Computer #Vision
Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications
Price:$65.99– $61.17
(as of Dec 24,2024 10:47:26 UTC – Details)
Publisher : Packt Publishing (November 27, 2020)
Language : English
Paperback : 824 pages
ISBN-10 : 1839213477
ISBN-13 : 978-1839213472
Item Weight : 3.1 pounds
Dimensions : 9.25 x 7.52 x 1.69 inches
In this post, we will delve into the world of modern Computer Vision with PyTorch, a powerful deep learning framework. We will explore key concepts in deep learning and demonstrate how to implement over 50 real-world image applications using PyTorch.Computer Vision is a field of artificial intelligence that enables computers to interpret and understand the visual world. With the advancements in deep learning and the availability of high-performance computing resources, Computer Vision has seen incredible progress in recent years.
PyTorch is a popular open-source deep learning framework that provides flexible tools and libraries for building and training deep neural networks. With PyTorch, you can easily implement complex deep learning models for Computer Vision tasks, such as image classification, object detection, image segmentation, and more.
In this post, we will cover a wide range of topics in modern Computer Vision, including:
– Introduction to deep learning and neural networks
– Convolutional Neural Networks (CNNs) for image classification
– Transfer learning and fine-tuning pre-trained models
– Object detection using Faster R-CNN and YOLO
– Semantic segmentation with U-Net and DeepLabv3
– Generative Adversarial Networks (GANs) for image synthesis
– And much more!Throughout the post, we will provide hands-on examples and code snippets to help you understand and implement these concepts in PyTorch. By the end of this post, you will have a solid understanding of modern Computer Vision techniques and be able to apply them to a wide range of real-world image applications.
So, if you are interested in exploring the cutting-edge of Computer Vision with PyTorch, stay tuned for our upcoming posts!
#Modern #Computer #Vision #PyTorch #Explore #deep #learning #concepts #implement #realworld #image #applications
