DeepLabCut™ is an efficient method for 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results across a broad collection of behaviours. This project will utilise the DeepLabCut package to analyse the behaviour of rats and mice as they are trained and tested on reward-based learning tasks designed to examine aspects of attention, memory and impulsive behaviour.
Honours and Minor Thesis projects
Displaying 211 - 220 of 220 honours projects.
Primary supervisor: Bioinformatics
Primary supervisor: Bioinformatics
Proteomics data generated by cutting-edge mass spectrometers play a crucial part in early disease diagnosis, prognosis and drug development in the biomedical sector. It can be used to understand the expression, structure, function, interactions and modifications of virtually any protein in any cell, tissue or organ. Moreover, proteomics can be used in conjunction with other “omics” technologies such as genomics, transcriptomics or metabolomics to further unravel the complexity of signalling pathways and other subcellular systems.
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Primary supervisor: KokSheik Wong
Multimedia content such as audio, image, and video are stored and transported in compressed forms. Various standards are designed to encode the content at the highest possible level while minimizing distortion. Some commonly used compression standards include MP3 for audio, JPEG for still image, H.264/AVC for video. Despite the vast differences in signal characteristics, most compression standards have two things in common: transformed-quantized coefficients and scale factor (quantization table in JPEG and AVC). The coefficients are usually coded as a product of sign_bit and magnitude.
Primary supervisor: Ong Huey Fang
Following the success of the Human Genome Project, the entire scientific community witnessed a large data explosion in genomics, which was also aided by advances in molecular biology technologies such as next-generation sequencing. These high-throughput technologies enable comprehensive molecular profiling of cancer cell lines, including gene expression. Regardless of the use of gene-based assays, they provide abundant genomic information for identifying participating genes (biomarkers) that contribute to the chemoresistance process in cancer cells.…
Primary supervisor: Wai Peng Wong
In our current day and age, there is an exponential growth in multimodal data, especially the transition of social media from text-based communications to video formats which can be observed with the rise of TikTok, Youtube, and Instagram Reels. This shift requires a shift in how we analyze multimodal data as we will have to move away from traditional text sentiment analysis such as TextCNN.
Primary supervisor: Raphaël C.-W. Phan
Cybersecurity researchers are contemplating how to best use the currently trending AI techniques to aid cybersecurity, beyond just for classification.
The aim of this Honours project is to get the student to work with the supervisors on the latest AI techniques to adapt them over for cybersecurity, building first on baseline approaches for which code is available.
Primary supervisor: Wai Peng Wong
This project will apply feature selection techniques for identifying features that can effectively predict the Logistics Performance Index (LPI), building upon our previously published work [1].
Primary supervisor: KokSheik Wong
As the number of mental health patients increases, the demand for qualified counselors is on the rise. However, training/practice sessions with actual patients are often limited, let alone meeting a sufficient number of patients of different personalities. This project aims to use large language models to simulate therapy sessions under certain predefined circumstances. This project is co-supervised by a collaborator from the Psychology department in Jeffrey Cheah School of Medicine and Health Sciences.
Primary supervisor: Raveendran A/L Paramesran
The application of AI in sports is widely researched as both coaches and players realise the significance of quantitative analysis that can be extracted from video matches. Detecting and segmenting in-play scenes in sport video
sequences is necessary in various applications such as quantitative game and performance analysis. In studies on video-based game and performance analysis of racket sports, much research efforts have been made to explore the relationships between predefined parameters and sports performance, and the methodologies for effective coaching.
Primary supervisor: Reuben Kirkham
(This is *not* a minor thesis or honours project, but a summer scholarship project advert only available to existing Monash taught students).
This project provides an opportunity to build on an existing funded project that focussed on document annotation using a web platform. The idea of this project is to build systems that can help humans add labels to documents more rapidly.