Automatic sound classification attracts increasing research attention owing to its vast applications, such as robot navigation, environmental sensing, musical instrument classification, medical diagnosis, and surveillance. Sound classification tasks involve the extraction of acoustic characteristics from the audio signals and the subsequent identification of different sound classes. In this project, we will explore diverse deep neural … full description “Deep Learning-based Environmental Sound Classification (available)”
Category: Bioinformatics
Predicting and Explaining Drug Toxicity with Graph Neural Networks (available)
This student research project focuses on predicting and explaining drug toxicity using advanced machine learning techniques, specifically Graph Neural Networks (GNNs). Graph Neural Networks are a modern, powerful class of machine learning models widely used across diverse fields, from chemistry to social networks. However, one of the major challenges with traditional GNNs is their “black-box” … full description “Predicting and Explaining Drug Toxicity with Graph Neural Networks (available)”
Video Action Classification (available)
Automatic interpretation of human actions from realistic videos attracts increasing research attention owing to its growing demand in real-world deployments such as biometrics, intelligent robotics, and surveillance. In this project, we will explore a variety of deep neural networks for video action classification, owing to their great efficiency in spatial-temporal feature learning.