Название: Deep Learning in Visual Computing and Signal ProcessingАвтор: Krishna Kant Singh, Vibhav Kumar Sachan
Издательство: Apple Academic Press/CRC Press
Год: 2023
Страниц: 289
Язык: английский
Формат: pdf (true)
Размер: 15.9 MB
An enlightening amalgamation of Deep Learning concepts with visual computing and signal processing applications, this new volume covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing.
The volume first lays out the fundamentals of Deep Learning as well as Deep Learning architectures and frameworks. It goes on to discuss Deep Learning in neural networks and Deep Learning for object recognition and detection models. It looks at the various specific applications of Deep Learning in visual and signal processing, such as in biorobotics, for automated brain tumor segmentation in MRI images, in neural networks for use in seizure classification, for digital forensic investigation based on Deep Learning, and more.
This book is a resource that can help readers enter and master the field of Deep Learning. The book focuses on the usage of Deep Learning in the field of visual computing and signal processing. The book is an amalgamation of Deep Learning concepts with visual computing and signal processing applications. It will provide readers a comprehensive knowledge of the field. This book provides information starting with the fundamental to the latest research being done in the field.
There are several books available in Deep Learning and Machine Learning. There is no such book available that focuses on the usage of Deep Learning specifically for visual computing and signal processing. It also provides the research applications of Deep Learning in visual computing and signal processing. Thus, this book is unique in terms of the topics and related contents it covers. Readers from many domains will be interested as it covers three major fields. Also, it will be appealing for the readers who tend to research in this field as the book covers latest research topics.
Today, Deep Learning (DL) is one of the most popular technologies in the world. In recent times, DL has been emerged as the most demanding technology due to its wide applicability and success rate in various application domains. The application of DL is growing very fast in several domains and has been resolving many real-world problems in the public interest. DL is also used in the new application areas where there is an immense need to find the solution for various issues. The DL method has been mainly categorized in deep supervised and unsupervised learning as we can see in the case of Machine Learning. But the DL methods have shown their outstanding performance in comparison to the traditional Machine Learning approaches. That is why DL is becoming more popular in the field of Computer Vision, machine translation, image processing, speech recognition, bioinformatics, medical imaging, and many others.
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