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ball » all (Expand Search), wall (Expand Search), fall (Expand Search)
drago » dragon (Expand Search), dragos (Expand Search), drag (Expand Search)
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1
Towards understanding genome regulation via high-resolution analysis of chromatin accessibility
Published 2023“…For both bulk and single-cell datasets, I show the robustness of EpiCall in peak calling down-sampled low-quality data, a significant advantage over current peak callers.…”
Thesis -
2
How do you predict your future movement and locations?
Published 2014“…This project serves to provide an analysis on GPS data and external information like the calls and messages of a person to predict his/her future movement and location. …”
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Final Year Project (FYP) -
3
Ionic liquid lubricity enhancement with bio-oil derived from microwave pyrolysis of bamboo
Published 2024“…The investigation focuses on the interaction between bio-oil, derived from raw bamboo (Phyllostachys edulis) through microwave pyrolysis at power levels between 500 and 800 W at 700 ∘C, and the protic ionic liquid, [Oley][Oleic]. …”
Article -
4
Streamoscope: A Low-Cost, Open-Source, USB-3-Capable Streaming Data Acquisition System for Low-Field MRI
Published 2024“…The Streamoscope can stream full-sample-rate raw MRI data into a computer to be processed in Python, enabling real time imaging. …”
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Thesis -
5
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Data for the ‘Orchid Observers’ project
Published 2017“…Once the authors’ research papers have been published, a full, cleaned set of the analysed data will be deposited. …”
Dataset -
7
Immune Checkpoint Blockade sensitivity and Progression-Free Survival associates with baseline CD8+ T cell clone size and cytotoxicity
Published 2021“…The cells contained within the expression matrices and Seurat objects have undergone full pre-processing and QC steps and are used for the analysis and figures in the linked manuscript. …”
Dataset -
8
Data analytics of air pollution data
Published 2018“…However, the data is presented as raw time series data and no analytics is provided. …”
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Final Year Project (FYP) -
9
Multi-facet in heterogeneous information network representation learning
Published 2020“…The process of converting raw HIN datasets into dense matrixes of lower dimensions while still preserving the network structure as much as possible is called graph embedding or representation learning, which is the very first step to be carried out before any algorithm could be applied on the network to study its structure or node relationships. …”
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Final Year Project (FYP) -
10
RanDumb: random representations outperform online continually learned representations
Published 2025“…Our primary contribution is empirically demonstrating that existing online continually trained deep networks produce inferior representations compared to a simple pre-defined random transforms. Our approach embeds raw pixels using a fixed random transform, approximating an RBF-Kernel initialized before any data is seen. …”
Conference item -
11
Detection of Magnetic Field Effects by Confocal Microscopy
Published 2020“…This dataset contains raw data and accompanying analysis used in the publication 'Detection of Magnetic Field Effects by Confocal Microscopy' by Dejean et al. …”
Dataset -
12
Compressed event sensing (CES) volumes for event cameras
Published 2024“…To address this issue, we propose a novel event representation called compressed event sensing (CES) volumes. CES volumes preserve the high temporal resolution of event streams by leveraging the sparsity property of events and the principles of compressed sensing theory. …”
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Journal Article -
13
CipherTrace: automatic detection of ciphers from execution traces
Published 2020“…The synthetic information can be categorized as raw (i.e., Platform-driven or Assembly-driven), or lifted (i.e., LLVM-driven). …”
Thesis -
14
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15
Indoor occupancy estimation using environmental parameters
Published 2017“…To perform occupancy estimation within the proposed framework, we present a novel technique called the Hybrid Feature- Scaled Extreme Learning Machine (HFS-ELM). …”
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Thesis-Doctor of Philosophy -
16
Tracking and detecting objects in image sequence
Published 2016“…The first piece of work addresses learning hierarchical features for visual object tracking by using deep learning. Previously, raw pixel values or hand-crafted features are used to represent target objects. …”
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Thesis