Recent Trends in Image Processing and Pattern Recognition 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 1-2, 2022, Revised Selected Papers

This book constitutes the refereed proceedings of the 5th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2022, held in Kingsville, TX, USA, in collaboration with the Applied AI Research Laboratory of the University of South Dakota, during December 01-02, 2022.

The 31 full papers included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: healthcare: medical imaging and informatics; computer vision and pattern recognition; internet of things and security; and signal processing and machine learning.

Healthcare: medical imaging and informatics.- Data Characterization for Reliable AI in Medicine.- Alzheimer’s Disease Detection using Ensemble Learning and Artificial Neural Networks.- Semi-supervised Multi-domain Learning for Medical Image Classification.- Significant CC400 functional brain parcellations based LeNet5 Convolutional Neural Network for Autism Spectrum Disorder detection.- 2D respiratory sound analysis to detect lung abnormalities.- Analyzing Chest X-Ray to Detect the Evidence of Lung Abnormality due to Infectious Disease.- Chest X-ray Image Super-resolution via Deep Contrast Consistent Feature Network.- A Novel Approach to Enhance Effectiveness of Image Segmentation Techniques on Extremely Noisy Medical Images.- Federated Learning for Lung Sound Analysis.- Performance Analysis of CNN and Quantized CNN Model for Rheumatoid Arthritis Identification using Thermal Image.- Image Processing and Pattern Recognitionof Micropores of Polysulfone Membrane for the Bio-separation of Viruses from Whole Blood.- An Extreme Learning Machine-basedAutoEncoder (ELM-AE)for denoising knee X-ray images and grading knee osteoarthritis severity.- Computer Vision and Pattern Recognition.- Motor Imagery Classification CombiningRiemannian Geometry and Artificial Neural Networks.- Autism Spectrum Disorder Detection using Transfer Learning with VGG 19, Inception V3 and DenseNet 201.- Shrimp Shape Analysis by a Chord LengthFunction Based Methodology.- Supervised Neural Networks for Fruit Identification.- Targeted Clean-Label Poisoning Attacks On Federated Learning.- Building Marathi SentiWordNet.- A computational study on calibrated VGG19 formultimodal learning and representation insurveillance.- Automated Deep Learning based approach for Albinism Detection.- A Deep learning-based regression scheme for angle estimation in image dataset.- The classification of Native and Invasive Speciesin North America: A Transfer Learning and Random Forest Pipeline.- Internet of Things and Security.- Towards a Digital Twin Integrated DLT and IoT-based Automated Healthcare Ecosystem.- Enabling Edge Devices using Federated Learning and Big Data for Proactive Decisions.- IoT and Blockchain oriented gender determination of Bangladeshi populations.- Federated Learning based secured computational offloading in cyber-physical IoST systems.- A Hybrid Campus Security System Combined ofFace, Number-plate, and Voice Recognition.- Signal Processing and Machine.- Single-trial detection of event-related potentials with artificial examples based on coloring transformation.- Identifying the relationship between hypothesis and premise.- Data Poisoning Attack by Label Flipping onSplitFed Learning.- A Deep Learning-powered voice-enabled mathtutor for kids.