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sspine » spine (Expand Search), supine (Expand Search), sspinge (Expand Search), ssspine (Expand Search)
pinned » finned (Expand Search), pingned (Expand Search), spinned (Expand Search)
spinae » spinal (Expand Search), spine (Expand Search), shinae (Expand Search), spingae (Expand Search), sspinae (Expand Search)
pin » ping (Expand Search), spin (Expand Search)
ling » long (Expand Search), line (Expand Search), link (Expand Search)
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A guide to being the elephant in the room : a study on the residual behaviours stemming from bodyweight stigma
Published 2020Get full text
Final Year Project (FYP) -
1503
Mu (em-power-you) : a jewelry brand inspired by the stories of different communities
Published 2021Get full text
Final Year Project (FYP) -
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Towards semantic, debiased and moment video retrieval
Published 2025“…Our approach tackles this challenge for the first time on long, fine-grained, and untrimmed egocentric videos, while existing methodologies target short, coarse-grained, and trimmed third-person videos. …”
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Thesis-Doctor of Philosophy -
1510
Towards optimal scheduling of deep learning training jobs in GPU clusters
Published 2025“…Second, it reuses the fine-tuning runtime of FMF workloads to reduce the significant context switch overhead. …”
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Thesis-Doctor of Philosophy -
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Supercreative : unleashing creative potential.
Published 2013Get full text
Final Year Project (FYP) -
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Image retrieval with deep learning
Published 2017“…Actions can be done to fine-tune the feature extractor with distorted images to see whether it will be more resilient to these distortion methods. …”
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Final Year Project (FYP) -
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Plasma enhanced chemical vapor deposition growth of vanadium dioxide
Published 2019“…To achieve high quality VO2 thin film on a soda lime glass substrate, understanding nucleation mechanism to fine tune the process condition is essential. Are discussed in this report. …”
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Final Year Project (FYP) -
1520
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data
Published 2024“…We conduct a broad range of experiments, covering zero-shot prompting, few-shot prompting, and instruction fine-tuning. The results indicate a promising yet limited performance of LLMs with zero-shot and few-shot prompt designs for mental health tasks. …”
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Article