Python
Artificial Intelligence
E-Commerce Fraud Detection Using Generated Data From BANKSIM Using Machine Learning
Evolving Malware and DDoS Attacks: Decadal Longitudinal Study
IBGS A Wearable Smart System to Assist Visually Challenged
Embedded, Artificial Intelligence(AI), Internet of Things(IoT), Social Cause, Artificial Intelligence, IoT
Integration of Traditional Knowledge and Modern Science: A Holistic Approach to Identify Medicinal Leaves for Curing Diseases
Interpretable Deep Learning Framework for Land Use and Land Cover Classification in Remote Sensing Using SHAP
LE-YOLO: Lightweight and Efficient Detection Model for Wind Turbine Blade Defects Based on Improved YOLO
Lung Nodule Detection in Medical Images Based on Improved YOLOv5
Python, Deep Learning, Generative AI, Projects, Artificial Intelligence, Deep Learning, Generative AI
Obfuscated Privacy Malware Classification Using Machine Learning and Deep Learning Techniques
Python, Cybersecurity, Deep Learning, Machine Learning, Artificial Intelligence, Cyber Security, Deep Learning, Machine Learning
Aim
The aim of this research is to develop an intelligent system capable of detecting and classifying obfuscated privacy malware into various categories and families. This system leverages machine learning and deep learning models trained on the CIC-MalMem-2022 dataset to improve accuracy and address the challenges posed by data imbalance and complex malware behaviour.
Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Product Recommendation System Using Large Language Model Llama 3
To develop a chatbot that integrates Retrieval-Augmented Generation (RAG) and Llama-3 API for product recommendation by leveraging a vector database with embeddings created using SBERT. This aim involves addressing limitations in traditional recommender systems, such as cold start problems and lack of personalization, by combining state-of-the-art language models with efficient data retrieval mechanisms.
