LE DUY TAM

The image retrieval system is based on content, utilizing Convolutional Neural Networks (CNN) and hashing. It employs a CNN to extract image features, which are then transformed into binary hash codes, representing each hash code as a binary vector. The input image is processed to obtain a binary hash code, which is then used to calculate the Hamming distance with the set of binary hash codes in the dataset. The system then suggests the top k images with the lowest Hamming distance compared to the input image. The primary dataset used for this system is the "fashion-productimages-dataset," sourced from Kaggle Link GitHub: https://github.com/DuyTam01/cbir_cnn_and_hash Link report: https://drive.google.com/file/d/1gQneaB2-ogFd8gQ4NXal56FSvRC_mJ7w/view Link poster: https://drive.google.com/file/d/1ja9Z_KMFg_jfz2CqmtgtPlA42dL30vU7/view;

ThanhLiWeb is a simple e-commerce web application developed using modern frontend technologies. The system allows users to view, filter, and interact with a list of products through a clean and responsive interface. It integrates state management with Redux, routing via React Router, and API interaction through Axios using a Mock-API backend. The UI is built with React Strap and Bootstrap to ensure responsiveness and user-friendliness. The project is deployed and accessible via GitHub Pages Link GitHub: https://github.com/DuyTam01/web_ThanhLi Link Demo: https://duytam01.github.io/web_ThanhLi/;