Advances in Deep Learning, Volume 2
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Beschreibung
This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. The book discusses the use of these advanced topics in selected applications like image classification, object detection, image steganography, protein secondary structure prediction, and gene expression data classification. Various challenges and future research directions falling under the scope of these topics are discussed.
This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. The book discusses the use of these advanced topics in selected applications like image classification, object detection, image steganography, protein secondary structure prediction, and gene expression data classification. Various challenges and future research directions falling under the scope of these topics are discussed.
Highlights novel ways of using advanced deep learning topics to solve real-world problems Offers insights into deep learning architectures and algorithms Elaborates on both basic and advanced concepts in deep learning
Autor*in
M. Arif Wani
Themen in »Advances in Deep Learning, Volume 2«
Deep Learning Deep Learning Architectures Ensemble Deep Learning Hybrid Deep Learning Approaches Lightweight Deep Learning Architectures Neural Architecture Search Image Steganography Using Deep Networks Object Detection Using Deep Networks Image Classification Using Deep Networks