Deep Learning in Visual Computing and Signal Processing PDF Download
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Author: Krishna Kant Singh
Publisher: CRC Press
ISBN: 1000565238
Category : Science
Languages : en
Pages : 289
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Book Description
Covers both the fundamentals and the latest concepts in deep learning Presents some of the diverse applications of deep learning in visual computing and signal processing Includes over 90 figures and tables to elucidate the text
Author: Krishna Kant Singh
Publisher: CRC Press
ISBN: 1000565238
Category : Science
Languages : en
Pages : 289
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Book Description
Covers both the fundamentals and the latest concepts in deep learning Presents some of the diverse applications of deep learning in visual computing and signal processing Includes over 90 figures and tables to elucidate the text
Author: Ragav Venkatesan
Publisher: CRC Press
ISBN: 1351650327
Category : Computers
Languages : en
Pages : 204
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Book Description
This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.
Author: Hassan Ugail
Publisher: CRC Press
ISBN: 1000625451
Category : Computers
Languages : en
Pages : 144
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Book Description
Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing. This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.
Author: Li Deng
Publisher:
ISBN: 9781601988140
Category : Machine learning
Languages : en
Pages : 212
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Book Description
Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
Author: Max A. Little
Publisher: Oxford University Press, USA
ISBN: 0198714939
Category : Computers
Languages : en
Pages : 378
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Book Description
Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.
Author: Radek Silhavy
Publisher: Springer Nature
ISBN: 3031705955
Category :
Languages : en
Pages : 534
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Book Description
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 012816087X
Category : Science
Languages : en
Pages : 348
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Book Description
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
Author: Kalaiselvi K.
Publisher: CRC Press
ISBN: 1003810403
Category : Technology & Engineering
Languages : en
Pages : 421
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Book Description
This book brings new smart farming methodologies to the forefront, sparked by pervasive applications with automated farming technology. New indigenous expertise on smart agricultural technologies is presented along with conceptual prototypes showing how the Internet of Things, cloud computing, machine learning, deep learning, precision farming, crop management systems, etc., will be used in large-scale production in the future. The necessity of available welfare systems for farmers’ well-being is also discussed in the book. It draws the conclusion that there is a greater need and demand today for smart farming methodologies driven by technology than ever before.
Author: Muhammad Younas
Publisher: Springer Nature
ISBN: 3031680057
Category :
Languages : en
Pages : 324
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Book Description
Author: George Bebis
Publisher: Springer Nature
ISBN: 3031479696
Category : Computers
Languages : en
Pages : 630
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Book Description
This volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA. The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as: Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture. Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster.
