An Intelligent Food Image Analysis System for the Hospitality Industry

Project Abstract

Null

Research Area

Machine Learning: Machine Learning (ML) research in Computer Science and Information Technology focuses on the development of algorithms and models that enable computers to learn from data and improve their performance over time without being explicitly programmed. It is a subset of Artificial Intelligence that uses statistical techniques to give machines the ability to learn patterns, make decisions, and predict outcomes based on data. Supervised learning, a key area of ML research, involves training models on labeled data, where the input-output relationships are predefined. This method is widely used for tasks such as classification (e.g., spam detection) and regression (e.g., predicting house prices). Unsupervised learning, on the other hand, involves finding hidden patterns in data without predefined labels, with clustering and association being typical applications in areas such as customer segmentation and anomaly detection. Reinforcement learning is another area of ML that focuses on teaching agents to make decisions by interacting with their environment and receiving feedback in the form of rewards or penalties. It is often applied in robotics, game playing, and autonomous systems, where continuous learning and adaptation are required.

Project Main Objective

• To create an AI-based system, which is capable of producing accurate cooking instruction, ingredient lists, and a nutrition-facts information directly from an image on food which is going to be used by Eusbett hotel.

Academic Year

2024/2025

Date Uploaded

Feb 3, 2026

Group Members

Null

Program Of Study

BSc Information Technology