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Full Description
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.
Contents
Deep learning models for classification of remotely sensed data of sugarcane.- Detection and Analysis of Wormhole Attacks in the AODV Routing Protocol with IEEE 802.11p for the Internet of Vehicles.- A Systematic Review of NLP Applications in Clinical Healthcare: Advancement and Challenges.- An Investigational Analysis of Automatic Speech Recognition on Deep Neural Networks and Gated Recurrent Unit Model.- Matched Filter and Kirsch's Template based approach for Retinal Vessel Segmentation.- Prediction of abnormality in kidney function using classification techniques and fuzzy systems.- Implementation of Parallel Applications on the Hypercube Topology by Using Multistage Network.- Integrating Artificial Intelligence for Adaptive Decision-Making in Complex System.- Qualitative Research Reasoning on Dementia Fore-cast using Machine Learning Techniques.- Implementation of Vision Transformers on SPECT Heart Dataset: A Comparative Study.- CSR U-Net: A Novel Approach for Enhanced Skin CancerLesion Image Segmentation.- Automatic Detection and Classification System for Mesothelioma Cancer using Deep Learning Models with HPO.- A systematic literature survey on IoT in Healthcare: Security and Privacy Threats.- Hybrid Deep Learning Framework for Glaucoma Detection Using Fundus Images.- Sunflower Optimization with Elite Learning Strategy (SFO-ELS) for Antenna Selection in Massive MIMO Sub Array Switching Architecture.- Machine Learning Models for Human Activity Recognition: A Comparative Study.
