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Advances in Deep Learning

ISBN-13: 9789811367939 / Angielski / Twarda / 2019 / 149 str.

M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal
Advances in Deep Learning M. Arif Wani Farooq Ahmad Bhat Saduf Afzal 9789811367939 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Advances in Deep Learning

ISBN-13: 9789811367939 / Angielski / Twarda / 2019 / 149 str.

M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal
cena 726,29
(netto: 691,70 VAT:  5%)

Najniższa cena z 30 dni: 693,97
Termin realizacji zamówienia:
ok. 22 dni roboczych
Bez gwarancji dostawy przed świętami

Darmowa dostawa!
Kategorie:
Technologie
Kategorie BISAC:
Computers > Database Administration & Management
Mathematics > Matematyka stosowana
Computers > Artificial Intelligence - Computer Vision & Pattern Recognition
Wydawca:
Springer
Seria wydawnicza:
Studies in Big Data
Język:
Angielski
ISBN-13:
9789811367939
Rok wydania:
2019
Wydanie:
2020
Ilość stron:
149
Waga:
0.41 kg
Wymiary:
23.39 x 15.6 x 1.12
Oprawa:
Twarda
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

Preface.- Introduction to Deep Learning.- Basic Deep Learning Models.- Training Basic Deep Learning Models.- Optimising Deep Learning Models.- Application of Deep Learning in Classification.- Application of Deep Learning in Segmentation.- Application of Deep Learning in Face Recognition.- Application of Deep Learning in Fingerprint Recognition.- Author's Index.

Prof. M. Arif Wani completed his M.Tech. in Computer Technology at the Indian Institute of Technology, Delhi and his PhD in Computer Vision at Cardiff University, UK. Currently, he is a Professor at the University of Kashmir, having previously served as a Professor at California State University Bakersfield. His main research interests are in gene expression datasets, face recognition techniques/algorithms, artificial neural networks and deep architectures. He has published many papers in reputed journals and conferences in these areas. He was honored with The International Technology Institute Award in 2002 by the International Technology Institute, California, USA. He is a member of many academic and professional bodies, e.g. the Indian Society for Technical Education, Computer Society of India, IEEE USA and Optical Society of America.

Dr. Farooq Ahmad Bhat completed his MPhil and PhD in Computer Science at the University of Kashmir. His dissertation focused on ‘Efficient and robust convolutional neural network based models for face recognition’. Currently, his main interests are in artificial intelligence, machine learning and deep learning, areas in which he has published many articles.

Dr. Saduf Afzal teaches at the Islamic University of Science and Technology, Kashmir, India. She completed her BCA, MCA, MPhil and PhD at the Department of Computer Science, University of Kashmir. She has also worked as an academic counselor for the MCA program at IGNOU University. Her main research interests are in machine learning, deep learning and neural networks. She has published many articles in high-impact journals and conference proceedings.

Dr. Asif Iqbal Khan currently works as a Lecturer in the Higher Education Department, Kashmir, India. He completed his MCA, MPhil and PhD at the Department of Computer Science, University of Kashmir. His main research interests are in machine learning, deep learning, and image processing. He is actively publishing in these areas.


This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.



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