Bangladesh Bangladesh Agriculture Biometric data standardization BYOL Cross-border Diabetes Dialect Education Emotion recognition;Accuracy;Translation;Automation;Text recognition;Data augmentation;Transformers;Natural language processing;Data models;Ensemble learning;Emotion Recognition;Data Augmentation;Bangla NLP;BanglaBERT;MultiBERT;Transformers;Back Translation Ethics Fanaroff-Riley Human Rights ICTD Immigrants July Uprising Land Use Land Cover LLM Natural language processing PACE Phishing;Feature extraction;Accuracy;Support vector machines;Classification algorithms;Runtime;Classification tree analysis;Rough sets;Radio frequency;Principal component analysis;Cyber security;feature selection;hybrid feature;machine learning;phishing;phishing websites;rough set theory;RSTHFS Predictive analysis Python Remote Sensing Risk factor analysis Semi-supervised Learning Servers;Vehicle dynamics;Optimization;Network topology;Real-time systems;Energy consumption;Digital twins;Delays;Edge computing;Computational modeling;Internet of Vehicle (IoV);Lyapunov (Ly) optimization;mobile edge computing (MEC);multiagent (MA) DDPG;task offloading SimCLR Support vector machines;Accuracy;Sensitivity;Psychology;Human factors;Nearest neighbor methods;Data models;Reliability;Random forests;Strain;Human Stress;Machine Learning;SMOTE Surveys;Bridges;Heuristic algorithms;Digital transformation;Pressing;Older adults;Particle swarm optimization;Informatics;Mobile computing;Bangladesh;caregiving;caregivers;elderly;localized services;mHealth;mobile app Tutor

Show all

2025

Tahmida, Tasmia; Pasha, Syed Tangim; Hassan, Mehedi; Islam, Ashraful; Amin, M. Ashraful

Integrating Supervised and Self-Supervised Models for an Enhanced PCOS Detection: A Data-Driven Approach with Machine Learning Perspective Proceedings Article

In: 2025 6th International Conference on Artificial Intelligence, Robotics and Control (AIRC), pp. 499-503, 2025.

Links | BibTeX | Tags: Training;Accuracy;Atmospheric modeling;Autoencoders;Supervised learning;Static VAr compensators;Machine learning;Data models;Vectors;Robots;Polycystic Ovary Syndrome;KagglePCOS Dataset;Supervised Learning;Self-Supervised Learning;Autoencoder;SimCLR;BYOL