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Deep learning applications

Kantardzic, Mehmed.

Deep learning applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning applicationsedited by M. Arif Wani, Mehmed Kantardzic, Moamar Sayed-Mouchaweh.
other author:	Wani, M. Arif.
Published:	Singapore :Springer Singapore :2020.
Description:	x, 178 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-981-15-1816-4
ISBN:	9789811518164$q(electronic bk.)

Deep learning applications
Deep learning applications[electronic resource] /edited by M. Arif Wani, Mehmed Kantardzic, Moamar Sayed-Mouchaweh. - Singapore :Springer Singapore :2020. - x, 178 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.10982194-5357 ;. - Advances in intelligent systems and computing ;176..

Trends in Deep Learning Applications -- Optimization Strategies -- Quasi-Newton Optimization Methods -- Application to Deep Reinforcement Learning -- Medical Image Segmentation using Deep Neural Networks with Pre-trained Encoders -- Enabling Robust and Autonomous Material handling in Logistics through applied Deep Learning Algorithms -- Performance metric -- Dataset creation -- Detecting Work Zones in SHRP2 NDS Videos Using Deep Learning Based Computer Vision -- Deep Learning Framework and Architecture Selection -- Action Recognition in Videos Using Multi-Stream Convolutional Neural Networks -- Ensemble of 3D Densely Connected Convolutional Network for Diagnosis of Mild Cognitive Impairment and Alzheimers disease.

This book presents a compilation of selected papers from the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2018), focusing on use of deep learning technology in application like game playing, medical applications, video analytics, regression/classification, object detection/recognition and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

ISBN: 9789811518164$q(electronic bk.)

Standard No.: 10.1007/978-981-15-1816-4doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .D447 2020

Dewey Class. No.: 006.31

Deep learning applications
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505 0 $a Trends in Deep Learning Applications -- Optimization Strategies -- Quasi-Newton Optimization Methods -- Application to Deep Reinforcement Learning -- Medical Image Segmentation using Deep Neural Networks with Pre-trained Encoders -- Enabling Robust and Autonomous Material handling in Logistics through applied Deep Learning Algorithms -- Performance metric -- Dataset creation -- Detecting Work Zones in SHRP2 NDS Videos Using Deep Learning Based Computer Vision -- Deep Learning Framework and Architecture Selection -- Action Recognition in Videos Using Multi-Stream Convolutional Neural Networks -- Ensemble of 3D Densely Connected Convolutional Network for Diagnosis of Mild Cognitive Impairment and Alzheimers disease.
520 $a This book presents a compilation of selected papers from the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2018), focusing on use of deep learning technology in application like game playing, medical applications, video analytics, regression/classification, object detection/recognition and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
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