Advanced Technologies in Electronics, Communications and Signal Processing: First EAI International Conference, ICATECS 2024, Hyderabad, India, July 2627, 2024, Proceedings, Part II [Pehme köide]

Machine Learning and Deep Learning Applications.- Optimizing Blood
Donation Operations with a PHP Driven Management System.- FIT FORMA: live
fitness tracking application with blaze pose.- Genetic Algorithm Driven
Hyperparameter Optimization for Precision Sickle Cell Disease Prognosis.-
Enhanced Weed Classification with a Custom CNN: Evaluating Optimizer
Performance.- A STRATEGY FOR SAFEGUARDING THE MOST FRAGILE RAIL TRANSPORT
SYSTEM IN THE EVENT OF AN ACCIDENT - TRACK SENTIAL.- Leveraging Transfer
Learning for Plant Identification with Limited Data: A MobileNet V2 Based
Approach.- Airline Passenger Satisfaction Analysis using Classifiers
of Computation Models and Explainable AI.- Classify Object Behavior to
Enhance the Safety of Autonomous Vehicles.- Bottom Bounce Analysis of
Multipath Acoustic Propagation in Deep Water.- Comparative Analysis of
Self-Supervised Monocular Depth Estimation and ORB-SLAM2 in Visual Perception
and Robotics.- Acoustic based Drone Detection using Machine Learning.-
Bifunctional Tunable Metasurface for Terahertz Shielding and Refractive Index
Sensing Using a Machine Learning Based Prediction Model.- Temporal Analysis
in Deep Learning-Based Recommender Systems for Predicting Plant Disease
Outbreaks.- Enhancing IoT Security: Multiclass Traffic Classification with
Advanced Machine Learning Algorithms.- Detection of Artificial Profiles on
Social Media Platforms Using Machine Learning and Natural Language
Processing.- Towards sustainable weed management using lightweight deep
learning model.- Enhancing Safety in Autonomous Vehicles Using Advanced Deep
Learning-Based Pothole Detection.- CalMeter: Food Recognition and Calorie
Estimation using Deep Learning.- Enhancing Web-Based Advanced Persistent
Threat Detection through Deep Learning Techniques.- Application of Machine
Learning Algorithms for Vegetable Quality Prediction.- Diabetic Retinopathy
Detection using Deep Learning.- Optimized Feature Selection for Motion Sensor
Based Human Activity Recognition with Machine Learning Techniques.- Enhancing
Spectrum Awareness in Cellular Networks through Deep Learning Approaches for
Efficient 5G-NR and LTE Signal Classification.- Advancements in Diabetes
Prediction: Integrating Machine Learning with Smart Sensor.- A Hybrid Deep
Learning Approach to X-Ray Diagnosis of Lung Diseases.- Transparency in Lung
Cancer Prediction: Integrating Explainable AI Techniques with Machine
Learning Models.- Accurate Prediction and Classification of Heart
failure using Machine learning algorithms and Interpretation
using Explainable AI.- Electric Vehicle Charging Stations: A Comparative
Study of Multiple Machine Learning Classifiers and Interpretation Using
Explainable AI.- Deep Learning for Urban Sound Classification: Using CNN and
YAMNet Model Integration.- MelanomaNet: Deep Learning for Skin Cancer
Diagnosis through Inception V3.- Deciphering Chronic Kidney Disease
Diagnosis: A Comparative Exploration of Computational Approaches with LIME
and SHAP Interpretation.- Exploring Seed Quality Assessment through
Convolutional Neural Networks and Generative Adversarial Networks.-
Tuberculosis Detection in Chest X-rays using Deep Learning Algorithms with
segmentation and data augmentation techniques.