Challenges and Applications for Implementing Machine Learning in Computer Vision

Challenges and Applications for Implemen

📁 Challenges and Applications for Implementing Machine Learning in Computer Vision

✍ Ramgopal Kashyap; A. V. Senthil Kumar 📂 Library 📅 2019 🏛 Engineering Science Reference 🌐 English

Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognitio

TensorFlow 2.0 Computer Vision Cookbook:

📁 TensorFlow 2.0 Computer Vision Cookbook: Implement machine learning solutions to overcome various computer vision challenges

✍ Jesús Martinez 📂 Library 📅 2021 🏛 Packt Publishing 🌐 English

<p><b>Get well versed with state-of-the-art techniques to tailor training processes and boost the performance of computer vision models using machine learning and deep learning techniques</b></p><h4>Key Features</h4><ul><li>Develop, train, and use deep learning algorithms for computer vision tasks u

TensorFlow 2.0 Computer Vision Cookbook:

📁 TensorFlow 2.0 Computer Vision Cookbook: Implement machine learning solutions to overcome various computer vision challenges

✍ Jesús Martinez 📂 Library 🏛 Packt Publishing 🌐 English

<p><span>Get well versed with state-of-the-art techniques to tailor training processes and boost the performance of computer vision models using machine learning and deep learning techniques</span></p><h4><span>Key Features</span></h4><ul><li><span><span>Develop, train, and use deep learning algorit

TensorFlow 2.0 Computer Vision Cookbook:

📁 TensorFlow 2.0 Computer Vision Cookbook: Implement machine learning solutions to overcome various computer vision challenges

✍ Jesús Martinez 📂 Library 🏛 Packt Publishing 🌐 English

<p><span>Get well versed with state-of-the-art techniques to tailor training processes and boost the performance of computer vision models using machine learning and deep learning techniques</span></p><h4><span>Key Features</span></h4><ul><li><span><span>Develop, train, and use deep learning algorit

Implementations and Applications of Mach

📁 Implementations and Applications of Machine Learning (Studies in Computational Intelligence, 782)

✍ Saad Subair (editor), Christopher Thron (editor) 📂 Library 📅 2020 🏛 Springer 🌐 English

<p><span>This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, incl

Algorithmic advances in Riemannian geome

📁 Algorithmic advances in Riemannian geometry and applications : for machine learning, computer vision, statistics, and optimization

✍ Minh, Ha Quang; Murino, Vittorio 📂 Library 📅 2016 🏛 Springer 🌐 English

This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using