Machine Learning for Intelligent Multimedia Analytics : Techniques and Applications (Studies in Big Data)

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Machine Learning for Intelligent Multimedia Analytics : Techniques and Applications (Studies in Big Data)

Kumar, Pardeep (EDT)/ Singh, Amit Kumar (EDT)

ウェブストア価格 ¥45,052（本体¥40,957）
Springer Verlag, Singapore（2022/01発売）
外貨定価 US$ 199.99
ポイント 409pt

オンデマンド(OD/POD)版です。キャンセルは承れません。

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製本 Paperback:紙装版/ペーパーバック版／ページ数 335 p.
言語 ENG
商品コード 9789811594946
DDC分類 006.31

Full Description

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.

Chapter 1. Secure Multimodal Access with 2D and 3D Ears.- Chapter 2. Efficient and Low Overhead Detection of Brain Diseases using Deep Learning based Sparse MRI Image Classiﬁcation.- Chapter 3. Continual Deep Learning Framework for Medical Media Screening and Archival.- Chapter 4. KannadaRes-NeXt: a Deep Residual Network for Kannada Numeral Recognition.- Chapter 5. Secure Image Transmission in Wireless Network using Conventional Neural Network and DOST.- Chapter 6. Robust General Twin Support Vector Machine with Pinball Loss Function.- Chapter 7. Noise Resilient Thresholding based on Fuzzy Logic and Non-linear Filtering.- Chapter 8. Deep Learning Methods for Audio Events Detection.- Chapter 9. A Framework for Multi-lingual Scene Text Detection using K-means++ and Memetic Algorithms.- Chapter 10. Recent Advancements in Medical Imaging: A Machine Learning Approach.- Chapter 11. Solving Image Processing Critical Problems using Machine Learning.- Chapter 12. Spoken Language Identificationof Indian Languages using MFCC Features.- Chapter 13. Performance Evaluation of One-Class Classifiers (OCC) for Damage Detection in Structural Health Monitoring.- Chapter 14. Brain Tumor Classification in MRI Images using Transfer Learning.- Chapter 15. Semantic based Vectorization Technique for Hindi Language.