Deep Learning In Computer Vision

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Deep Learning For Computer Vision

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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2019-04-04

Deep Learning For Computer Vision written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-04 with Computers categories.

Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.

Deep Learning In Computer Vision

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Author : Mahmoud Hassaballah
language : en
Publisher: CRC Press
Release Date : 2020-03-23

Deep Learning In Computer Vision written by Mahmoud Hassaballah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-23 with Computers categories.

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.

Deep Learning For Computer Vision

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Author : Jyotsnarani Tripathy
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-09-05

Deep Learning For Computer Vision written by Jyotsnarani Tripathy and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-05 with Computers categories.

Jyotsnarani Tripathy, Assistant Professor, Department of CSE-AIML & IoT, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology (VNRVJIET), Hyderabad, Telangana, India. Dr.M.Kamal, Assistant Professor, Department of Computer Science, Jamal Mohamed College (Autonomous), Tiruchirappalli, Tamil Nadu, India. G.Ashalatha, Assistant Professor, Department of Artificial Intelligence & Data Science, CSE-Cyber Security, Data Science, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering &Technology (VNR VJIET), Hyderabad, Telangana, India. Mrs.EMN.Sharmila, Research Scholar, Department of Computer Science, CIRD Research Centre (Approved by University of Mysore), Bengaluru, Karnataka, India.

Advances In Deep Learning And Computer Vision

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Author : Dr. Jagadeesh Kumar
language : en
Publisher: Xoffencerpublication
Release Date : 2024-12-18

Advances In Deep Learning And Computer Vision written by Dr. Jagadeesh Kumar and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Computers categories.

Computer Vision (CV) can be defined as “the hypothesis and innovation for building artificial frameworks that acquire data from pictures or multi-dimensional information.” A more straightforward clarification is that computer vision endeavors to take care of similar issues you can unravel with your own one of kind eyes. For instance, in case you're driving and you see a kid run into the street, your mind will rapidly translate the kid in the street in front of you, that it's perilous, and that you ought to quickly brake to abstain from hitting the kid. That is one of the issues self-driving vehicle engineers are presently striving to comprehend by the methods of computer vision. The method requires being competent of realizing object recognition, which can be subdivided into three varieties: object classification, identification, and detection. Object Classification is everywhere you have a little recently learned objects that you need to have the option to perceive in a picture. Characterizing a representation photograph as having individual's face in it is a model object classification, arranged that this photograph contains a face in it. Object Identification is the recognition of a specific instance of an object. For example, being able to identify that there are two faces in an image and that one is John and the other is Sarah is an example of object identification. Object Detection is the ability to identify that there’s an object in an image. This is typically used for things like automatic toll roads where you want to know when a new object has entered the frame so you can take a scan the license plate. Connecting this to the self-driving car problem, if you think to how the human brain would solve this problem, it would have to answer the same questions: In order for the situation to be dangerous, we would have to both identify that there is a child (object) in or approaching the road. Identify that the child in the road is something that we should avoid. You would also want to identify other objects, like trash, soccer ball, bike, etc., where you don’t necessarily need evasive action. In other words, Computer Vision is the field of study that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos. The problem of computer vision appears simple because it is trivially solved by people, even very young children. Nevertheless, it largely remains an unsolved problem based both on the limited understanding of biological vision and because of the complexity of vision perception in a dynamic and nearly infinitely varying physical world.

Deep Learning

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Author : Rob Botwright
language : en
Publisher: Rob Botwright
Release Date : 2024

Deep Learning written by Rob Botwright and has been published by Rob Botwright this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Computers categories.

Introducing the Ultimate AI Book Bundle: Deep Learning, Computer Vision, Python Machine Learning, and Neural Networks Are you ready to embark on an exhilarating journey into the world of artificial intelligence, deep learning, and computer vision? Look no further! Our carefully curated book bundle, "DEEP LEARNING: COMPUTER VISION, PYTHON MACHINE LEARNING AND NEURAL NETWORKS," offers you a comprehensive roadmap to AI mastery. BOOK 1 - DEEP LEARNING DEMYSTIFIED: A BEGINNER'S GUIDE 🚀 Perfect for beginners, this book dismantles the complexities of deep learning. From neural networks to Python programming, you'll build a strong foundation in AI. BOOK 2 - MASTERING COMPUTER VISION WITH DEEP LEARNING 🌟 Dive into the captivating world of computer vision. Unlock the secrets of image processing, convolutional neural networks (CNNs), and object recognition. Harness the power of visual intelligence! BOOK 3 - PYTHON MACHINE LEARNING AND NEURAL NETWORKS: FROM NOVICE TO PRO 📊 Elevate your skills with this intermediate volume. Delve into data preprocessing, supervised and unsupervised learning, and become proficient in training neural networks. BOOK 4 - ADVANCED DEEP LEARNING: CUTTING-EDGE TECHNIQUES AND APPLICATIONS 🔥 Ready to conquer advanced techniques? Learn optimization strategies, tackle common deep learning challenges, and explore real-world applications shaping the future. 🎉 What You'll Gain: · A strong foundation in deep learning · Proficiency in computer vision · Mastery of Python machine learning · Advanced deep learning skills · Real-world application knowledge · Cutting-edge AI insights 📚 Why Choose Our Book Bundle? · Expertly curated content · Beginner to expert progression · Clear explanations and hands-on examples · Comprehensive coverage of AI topics · Practical real-world applications · Stay ahead with emerging AI trends 🌐 Who Should Grab This Bundle? · Beginners eager to start their AI journey · Intermediate learners looking to expand their skill set · Experts seeking advanced deep learning insights · Anyone curious about AI's limitless possibilities 📦 Limited-Time Offer: Get all four books in one bundle and save! Don't miss this chance to accelerate your AI knowledge and skills. 🔒 Secure Your AI Mastery: Click "Add to Cart" now and embark on an educational adventure that will redefine your understanding of artificial intelligence. Your journey to AI excellence begins here!

Deep Learning For Computer Vision

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Author : Rajalingappaa Shanmugamani
language : en
Publisher:
Release Date : 2018

Deep Learning For Computer Vision written by Rajalingappaa Shanmugamani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with COMPUTERS categories.

Advanced Methods And Deep Learning In Computer Vision

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Author : E. R. Davies
language : en
Publisher: Academic Press
Release Date : 2021-11-09

Advanced Methods And Deep Learning In Computer Vision written by E. R. Davies and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-09 with Technology & Engineering categories.

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. - Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field - Illustrates principles with modern, real-world applications - Suitable for self-learning or as a text for graduate courses

Domain Adaptation In Computer Vision With Deep Learning

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Author : Hemanth Venkateswara
language : en
Publisher: Springer Nature
Release Date : 2020-08-18

Domain Adaptation In Computer Vision With Deep Learning written by Hemanth Venkateswara and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Computers categories.

This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation. Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.

Deep Learning And Computer Vision Models And Biomedical Applications

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Author : Uma N. Dulhare
language : en
Publisher: Springer Nature
Release Date : 2025-03-08

Deep Learning And Computer Vision Models And Biomedical Applications written by Uma N. Dulhare and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-08 with Computers categories.

This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.

Hands On Java Deep Learning For Computer Vision

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Author : Klevis Ramo
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-02-21

Hands On Java Deep Learning For Computer Vision written by Klevis Ramo and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Computers categories.

Leverage the power of Java and deep learning to build production-grade Computer Vision applications Key FeaturesBuild real-world Computer Vision applications using the power of neural networks Implement image classification, object detection, and face recognitionKnow best practices on effectively building and deploying deep learning models in JavaBook Description Although machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning. The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The book is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models. By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy. What you will learnDiscover neural networks and their applications in Computer VisionExplore the popular Java frameworks and libraries for deep learningBuild deep neural networks in Java Implement an end-to-end image classification application in JavaPerform real-time video object detection using deep learningEnhance performance and deploy applications for productionWho this book is for This book is for data scientists, machine learning developers and deep learning practitioners with Java knowledge who want to implement machine learning and deep neural networks in the computer vision domain. You will need to have a basic knowledge of Java programming.