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Deep learning in visual computing and signal processing

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep learning in visual computing and signal processing/ edited by Krishna Kant Singh ... [et al.]
其他作者:	Singh, Krishna Kant
出版者:	Palm Bay, FL :Apple Academic Press, : 2023.,
面頁冊數:	1 online resource.
內容註:	Deep learning architecture and framework / Ashish Tripathi, Shraddha Upadhaya, Arun Kumar Singh, Krishna Kant Singh, Arush Jain, Pushpa Choudhary, and Prem Chand Vashist -- Deep learning in neural networks : an overview / Vidit Shukla and Shilpa Choudhary -- Deep learning current trends and techniques / Bharti Sharma, Arun Balodi, Utku Kose, and Akansha Singh.
標題:	Computer vision. -
電子資源:	https://www.taylorfrancis.com/books/9781003277224
ISBN:	9781003277224

Deep learning in visual computing and signal processing
Deep learning in visual computing and signal processing[electronic resource] /edited by Krishna Kant Singh ... [et al.] - 1st ed. - Palm Bay, FL :Apple Academic Press,2023. - 1 online resource.

Includes bibliographical references and index.

Deep learning architecture and framework / Ashish Tripathi, Shraddha Upadhaya, Arun Kumar Singh, Krishna Kant Singh, Arush Jain, Pushpa Choudhary, and Prem Chand Vashist -- Deep learning in neural networks : an overview / Vidit Shukla and Shilpa Choudhary -- Deep learning current trends and techniques / Bharti Sharma, Arun Balodi, Utku Kose, and Akansha Singh.

"This new volume, Deep Learning in Visual Computing and Signal Processing, 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. Key features : 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, and includes over 90 figures and tables to elucidate the text. An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this valuable resource will serve as a guide for researchers, engineers, and students who want to have a quick start on learning and/or building deep learning systems. It provides a good theoretical and practical understanding and complete information and knowledge required to understand and build deep learning models from scratch"--

ISBN: 9781003277224

LCCN: 2022016048Subjects--Topical Terms:

540671
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.3/7

Deep learning in visual computing and signal processing
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245 0 0 $a Deep learning in visual computing and signal processing $h [electronic resource] / $c edited by Krishna Kant Singh ... [et al.]
250 $a 1st ed.
260 $a Palm Bay, FL : $b Apple Academic Press, $c 2023.
300 $a 1 online resource.
504 $a Includes bibliographical references and index.
505 2 $a Deep learning architecture and framework / Ashish Tripathi, Shraddha Upadhaya, Arun Kumar Singh, Krishna Kant Singh, Arush Jain, Pushpa Choudhary, and Prem Chand Vashist -- Deep learning in neural networks : an overview / Vidit Shukla and Shilpa Choudhary -- Deep learning current trends and techniques / Bharti Sharma, Arun Balodi, Utku Kose, and Akansha Singh.
520 $a "This new volume, Deep Learning in Visual Computing and Signal Processing, 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. Key features : 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, and includes over 90 figures and tables to elucidate the text. An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this valuable resource will serve as a guide for researchers, engineers, and students who want to have a quick start on learning and/or building deep learning systems. It provides a good theoretical and practical understanding and complete information and knowledge required to understand and build deep learning models from scratch"-- $c Provided by publisher.
588 $a Description based on print version record and CIP data provided by publisher; resource not viewed.
650 0 $a Computer vision. $3 540671
650 0 $a Signal processing $x Digital techniques. $3 624853
650 0 $a Deep learning (Machine learning) $3 3538509
700 1 $a Singh, Krishna Kant $q (Telecommunications professor) $3 3730943
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