Paradigm Shifts in Communication, Embedded Systems, Machine Learning, and Signal Processing

Third International Conference, PCEMS 2024, Nagpur, India, November 11–12, 2024, Revised Selected Papers, Part I

AvDeep Gupta,Vipin Kamble

Häftad, Engelska, 2025

Del 2490 i serien Communications in Computer and Information Science

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Beskrivning

The papers present recent research in the areas of communication, antenna, computer vison, medical image analysis, deep learning, AI based systems and applications, classification problem, embedded system and IoT, etc.

Produktinformation

Utgivningsdatum:2025-08-26
Mått:155 x 235 x 28 mm
Vikt:762 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:481
Förlag:Springer International Publishing AG
ISBN:9783031905797

Utforska kategorier

Innehållsförteckning

Tiny-YOLOv3 and SSD: Performance Evaluation for Human Detection in Crowded Images Under Various Conditions.- Optimizing Ultra-Wideband Antenna Design Using Deep Learning Models: A Comparative Study of DBN-ELM and PSO-DBN Approaches.- A Comprehensive Analysis and Recommendations for Fusion of Feature Vectors.- Adaptive Tactile Therapy system for children with Autism Spectrum Disorder.- Spam Detection: A Binary Classification Approach in Machine Learning.- Hospital Patient Monitoring and Fall Prediction System Using Medical Intranet of Things (MIoT).- Predicting Mortality Rates: A Regression Approach.- Deployment of MobileNet SSD Model for Real-time Autonomous Waste Detection and Collection.- Clustering analysis of high-tech startups using machine learning.- AI Enhanced Drug Recommendation System for Women.- Detection algorithms for fast moving targets in FMCW based Radar.- Improvement of Iconicity in Signed and Spoken Vocabulary through Convolutional Neural Network.- Predicting Diamond Prices Using Regression in Machine Learning.- Localizing and Classifying Kannada Texts Using a YOLO-Based Approach.- Improved DeHazing using novel CycleGAN algorithm.- Classification of Heart Sound Signals using Spectral Features for Diagnosis of Heart Abnormality.- Classification of Marine Organisms Using Deep Learning Method.- Enhanced Human Decision-Making Model for Iowa Gambling Task.- Iterative Sparse Inverse Covariance Estimation for Enhanced Skin Cancer Classification using VGG-19 with Batch Normalization.- Multi-modal based Sentiment Analysis Web Application using Flask and Deep Learning Models.- Enhancing Accuracy & Efficiency Analysis for Emotion detection & Prediction using Deep Learning model.- Devnagari Sign Language Recognition with LSTM-based RNN.- Convolutional Recurrent Neural Network Architecture for Firewall Anomaly Detection.- Enhancing Ear Detection for Biometric Systems Using YOLOv9.- Automatic Sporadic colonic hamartoma characterisation using Narrow Band Imaging Colonoscopy.- Deep Learning-Based Classification of Hyperplastic and Adenoma Polyps.- Deep Learning-Based Rainfall-Runoff Modeling for Flood Forecasting: Case study in Krishna River.- Physiological Signal Mapping: PPG-TO-ECG Conversion using BiLSTM.- Ensemble of Machine Learning and Deep Learning for Intraday Stock Trading Decision in Quantitative Finance.- Adaptive Graph Matching for Unsupervised Person Re-Identification in Video Surveillance.- ILRSEM: Design of an Incremental Learning Model for enhancing Resource Scheduling Efficiency of Mobile Edge Deployments.- Comparative analysis of performance of different Deep architectures for histopathology image segmentation to detect liver disease.- Finger Knuckle and Fingerprint based person authentication: Siamese Networks based approach.- Hypertension detection with Machine Learning classifiers using PPG signals.- Automated Diagnosis of Coronary Artery Disease and Myocardial Infarction Using Optimal Anti-symmetric Wavelet-Based Features.- Integrating Handcrafted Textural and Deep Learning Features for Improved Multi-Class Lung Disease Classification in Computed Tomography Imaging.- Xception-Based Face Anti-Spoofing Approach for Secure Biometric Authentication.- Gesture prediction using Surface-EMG signals.