Data Science

图书简介

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.

A Deep Learning Technique for Real-Time Active Car Tracking with Quadrotor Luiz Gustavo Miranda Pinto, Wander Mendes Martins and Alexandre Carlos Brandão Ramos (Federal University of Itajuba – Unifei, Brazil).- On fusion of NIR and VW information for cross-spectral iris matching Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran and Pawan Dubey (National Institute of Technology Delhi, Delhi, India).- Spark Enhanced Framework for Medical Phrase Embedding using Deep Neural Network Amol Bhopale and Ashish Tiwari (Visvesvaraya National Institute of Technology, Nagpur, India) .- Performance Analysis of big.LITTLE System with various Branch Prediction Schemes Froila Rodrigues and Nitesh Guinde (Goa College of Engineering, Farmagudi, Ponda , GoaIndia) .- Two-stage Credit Scoring Model based on Evolutionary Feature Selection and Ensemble Neural Networks Diwakar Tripathi, Damodar Reddy Edla, Annushri Bablani and Venkatanareshbabu Kuppili (Madanapalle Institute of Technology

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Data Science（Transactions on Computer Systems and Networks） 数据科学：理论、算法与应用 计算机科学技术基础学科

Data Science（Transactions on Computer Systems and Networks）

数据科学：理论、算法与应用
计算机科学技术基础学科