Python
Plant Disease Detection and Classification by Deep Learning: A Review
Predictive Analytics on Diabetes Data using Machine Learning Techniques
Quantum Safe Multi-Factor User Authentication Protocol for Cloud-Assisted Medical IoT
Aim:
To design and implement a Quantum-Safe Multi-Factor User Authentication Protocol for Cloud-Assisted Medical IOT systems, ensuring secure, privacy-preserving, and tamper-resistant access to sensitive healthcare data, even against future quantum-computing attacks, by integrating post-quantum cryptography.
ReACT_OCRS: An AI-Driven Anonymous Online Reporting System Using Synergized Reasoning and Acting in Language Models
Real-Time Prediction of Taxi Demand Using Recurrent Neural Networks
Sleep Apnea Detection From Single-Lead ECG: A Comprehensive Analysis of Machine Learning and Deep Learning Algorithms
Smart Electricity Meter Monitoring and Prediction using iSocket
Toward Fast and Accurate Violence Detection for Automated Video Surveillance Applications
Whale and Dolphin Classification
The proposed method involves a multi-step process to classify whale and dolphin species from images. First, the dataset is collected and pre-processed to ensure high-quality input data. The VGG16 model is used to extract features from the images, capturing complex patterns and details. These features are then used to train a Support Vector Machine (SVM) model, which excels in binary and multi-class classification tasks.
