Kumar P., Singh A.K. (Eds.) Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications

Springer, 2021. — 341 p. — (Studies in Big Data). — ISBN: 978-981-15-9491-5.This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image, audio, video, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling comprehensive visual classification to fill the semantic gap by exploring large-scale data, offering a promising frontier for detailed multimedia understanding, as well as extract patterns and making effective decisions by analyzing the large collection of data.Secure Multimodal Access with 2D and 3D Ears
Efficient and Low Overhead Detection of Brain Diseases Using Deep Learning-Based Sparse MRI Image Classification
Continual Deep Learning Framework for Medical Media Screening and Archival
KannadaRes-NeXt: A Deep Residual Network for Kannada Numeral Recognition
Secure Image Transmission in Wireless Network Using Conventional Neural Network and DOST
Robust General Twin Support Vector Machine with Pinball Loss Function
Noise Resilient Thresholding Based on Fuzzy Logic and Non-linear Filtering
Deep Learning Methods for Audio Events Detection
A Framework for Multi-lingual Scene Text Detection Using K-means++ and Memetic Algorithms
Recent Advancements in Medical Imaging: A Machine Learning Approach
Solving Image Processing Critical Problems Using Machine Learning
Spoken Language Identification of Indian Languages Using MFCC Features
Performance Evaluation of One-Class Classifiers (OCC) for Damage Detection in Structural Health Monitoring
Brain Tumor Classification in MRI Images Using Transfer Learning
Semantic-Based Vectorization Technique for Hindi Language