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Advances in Data-Driven Computing and Intelligent Systems Selected Papers from ADCIS 2023, Volume 1
Title
Advances in Data-Driven Computing and Intelligent Systems [electronic resource] : Selected Papers from ADCIS 2023, Volume 1 / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish C. Bansal.
ISBN
9789819995240
Edition
1st ed. 2024.
Publication
Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Physical Description
1 online resource (XIX, 551 p.) 238 illus., 177 illus. in color.
Local Notes
Access is available to the Yale community.
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Access restricted by licensing agreement.
Summary
This book is a collection of best-selected research papers presented at the International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2023) held at BITS Pilani, K K Birla Goa Campus, Goa, India, during September 21-23, 2023. It includes state-of-the-art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book is useful for academicians, research scholars, and industry persons.
Variant and related titles
Springer ENIN.
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Format
Books / Online
Language
English
Added to Catalog
March 01, 2024
Series
Lecture Notes in Networks and Systems, 891
Contents
Influences of specimen and fiber sizes on the direct tensile resistance of ultra-high-performance fiber-reinforced concretes
Conceptual Model for Data Collection and Processing in a Smart Medical Ward
Parts-of-Speech Tagger in Assamese using LSTM and Bi-LSTM
Detection of Explicit Lyrics in Hindi Music Using Different Machine Learning Algorithms
Does the Resilience learning game foster workforce open innovation and sustainability attributes? Empirical evidence from Greek food industry
Seizure Detection by Analyzing EEG Signals Using Deep Learning Networks
Enhancing Intelligent Video Surveillance: Deep Learning Approaches for Human Anomalous Behavior Recognition
GujFormer: A Vision Transformer Based Architecture for Gujarati Handwritten Character Recognition
Prediction of Soil Properties for Agriculture using Ensemble Learning Techniques/- Classification of organic and recyclable waste using a Deep learning approach
Machine Learning and its Application in Food Safety
ISO/IEC 27001 Standard: Analytical and Comparative Overview
Hybrid Deep Learning based Potato and Tomato Leaf Disease Classification
Anti-Forensic Analysis for Image Splicing Detection through Advanced Filters
Classification and prediction of vibration natural frequencies of a circular plate using Chladni patterns and deep learning techniques
Multi-Sensor Data Fusion and Deep Machine Learning Models based Mental Stress Detection System
Segmentation-based Transformer Network for Automated Skin Disease Detection.
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