This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.

Table of Contents

Part I Theory and Concepts

1 Active Learning for Network Intrusion Detection

2 Educational Data Mining Using Base (Individual) and Ensemble Learning Approaches to Predict the Performance of Students

3 Patient's Medical Data Security via Bi Chaos Bi Order Fourier Transform

4 Nepali Word-Sense Disambiguation Using Variants of Simplified Lesk Measure

5 Performance Analysis of Big.LITTLE System with Various Branch Prediction Schemes

6 Global Feature Representation Using Squeeze, Excite, and Aggregation Networks (SEANet)

7 Improved Single Image Super-resolution Based on Compact Dictionary Formation and Neighbor Embedding Reconstruction

8 An End-to-End Framework for Image Super Resolution and Denoising of SAR Images

Part II Models and Algorithms

9 Analysis and Deployment of an OCR- SSD Deep Learning Technique for Real-Time Active Car Tracking and Positioning on a Quadrotor

10 Palmprint Biometric Data Analysis for Gender Classification Using Binarized Statistical Image Feature Set

11 Recognition of Sudoku with Deep Belief Network and Solving with Serialisation of Parallel Rule-Based Methods and Ant Colony Optimisation

12 Novel DWT and PC-Based Profile Generation Method for Human Action Recognition

13 Ripeness Evaluation of Tobacco Leaves for Automatic Harvesting: An Approach Based on Combination of Filters and Color Models

14 Automatic Deep Learning Framework for Breast Cancer Detection and Classification from H&E Stained Breast Histopathology Images

15 An Analysis of Use of Image Processing and Neural Networks for Window Crossing in an Autonomous Drone

16 Analysis of Features in SAR Imagery Using GLCM Segmentation Algorithm

Part Ill Applications and Issues

17 Offline Signature Verification Using Galois Field-Based Texture Representation

18 Face Recognition Using 3D CNNs

19 Fog Computing-Based Seed Sowing Robots for Agriculture

20 An Automatic Tumor Identification Process to Classify MRI Brain Images

21 Lane Detection for Intelligent Vehicle System Using Image Processing Techniques

22 An Improved DCNN Based Facial Micro-expression Recognition System

23 Selective Deep Convolutional Framework for Vehicle Detection in Aerial Imagery

24 Exploring Source Separation as a Countermeasure for Voice Conversion Spoofing Attack

25 Statistical Prediction of Facial Emotions Using Mini Xception CNN and Time Series Analysis

26 Identification of Congestive Heart Failure Patients Through Natural Language Processing

About the Author

Gyanendra K. Verma is currently Assistant Professor at Department of Information Technology, National Institute of Technology Raipur, India. He has completed his B. Tech.