About the Book:
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 or classification, object detection or 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.
Table of Contents
Trends in Deep Learning Applications Quasi-Newton Optimization Methods for Deep Learning Applications Medical Image Segmentation Using Deep Neural Networks with Pre-trained Encoders Ensemble of 3D Densely Connected Convolutional Network for Diagnosis of Mild Cognitive Impairment and Alzheimer-s Disease Detecting Work Zones in SHRP2 NDS Videos Using Deep Learning Based Computer Vision Action Recognition in Videos Using Multi-stream Convolutional Neural Networks Deep Active Learning for Image Regression Deep Learning Based Hazard Label Object Detection for Lithium-ion Batteries Using Synthetic and Real Data Enabling Robust and Autonomous Materialhandling in Logistics Through Applied Deep Learning Algorithms
