A5086171825- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Machine Learning and Algorithms
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Human Pose and Action Recognition
- Sparse and Compressive Sensing Techniques
- Mosquito-borne diseases and control
- Retinal Imaging and Analysis
- Video Analysis and Summarization
- Brain Tumor Detection and Classification
- Medical Image Segmentation Techniques
- Advanced Graph Neural Networks
- Data Stream Mining Techniques
- Image Retrieval and Classification Techniques
- Emotion and Mood Recognition
- Malaria Research and Control
- Algorithms and Data Compression
- Advanced Neural Network Applications
- Neonatal and fetal brain pathology
- Cutaneous Melanoma Detection and Management
- Parasites and Host Interactions
- Non-Invasive Vital Sign Monitoring
- Imbalanced Data Classification Techniques
- EEG and Brain-Computer Interfaces
Dublin City University
2020-2025
German Research Centre for Artificial Intelligence
2021-2022
Max Planck Institute for Informatics
2022
University of Wisconsin–Madison
2014-2021
Oxford University Clinical Research Unit
2019-2020
Wellcome Trust
2020
Ho Chi Minh City University of Science
2017-2019
Université de Sherbrooke
2015-2016
Telomere maintenance by the telomerase reverse transcriptase requires a noncoding RNA subunit that acts as template for synthesis of telomeric repeats. In humans, (hTR) is non-polyadenylated transcript produced from an independent transcriptional unit. As yet, mechanism and factors responsible hTR 3' end processing have remained largely unknown. Here, we show matured via polyadenylation-dependent pathway relies on nuclear poly(A)-binding protein PABPN1 poly(A)-specific RNase PARN. Depletion...
Developing interactive lifelog retrieval systems is a growing research area. There are many international competitions for that encourage researchers to build effective can address the multimodal challenge of lifelogs. The Lifelog Search Challenge (LSC) was first organised in 2018 and currently only benchmarking evaluation systems. Participating should have an accurate search engine user-friendly interface help users retrieve relevant content. In this paper, we upgrade our previous MyScéal,...
The Lifelog Search Challenge (LSC) is an interactive benchmarking evaluation workshop for lifelog retrieval systems. challenge was first organised in 2018 aiming to find the system that can quickly retrieve relevant images a given semantic query. This paper provides analysis of performance all 17 systems participating 4th LSC held at 2021 Annual ACM International Conference on Multimedia Retrieval (ICMR). LSC'21 largest effort comparing different approaches seen thus far. Findings from...
Building an interactive retrieval system for lifelogging contains many challenges due to massive multi-modal personal data besides the requirement of accuracy and rapid response such a tool. The Lifelog Search Challenge (LSC) is international lifelog competition that inspires researchers develop their systems cope with evaluates effectiveness solutions. In this paper, we upgrade our previous Myscéal present 2.0 LSC'21 improved features inspired by novice users experiments. experiments show...
Multi-Camera Multi-Object Tracking is currently drawing attention in the computer vision field due to its superior performance real-world applications such as video surveillance with crowded scenes or wide spaces. In this work, we propose a mathematically elegant multi-camera multiple object tracking approach based on spatial-temporal lifted multicut formulation. Our model utilizes state-of-the-art tracklets produced by single-camera trackers proposals. As these may contain ID-Switch errors,...
Automatic segmentation of major brain tissues from high-resolution magnetic resonance images (MRIs) plays an important role in clinical diagnostics and neuroscience research. In this paper, we present a novel approach to extract including gray matter, white matter cerebrospinal fluid by using Gaussian mixture models (GMMs), Convolution neural networks (CNNs) Deep (DNNs). GMMs are applied classify voxels which have distinct intensity information easy recognize while DNNs CNNs treating similar...
The Lifelog Search Challenge (LSC), is an annual comparative bench-marking activity for comparing approaches to interactive retrieval from multi-modal lifelogs. Being search challenge, issues such as accuracy, speed and usability of inter-faces are key challenges that must be addressed by every participant. In this paper, we introduce Myscéal, lifelog engine designed support novice users retrieve items interest a large multimodal lifelog. Additionally, also anew similarity measure called...
Increasing the throughput of Transformer architecture, a foundational component used in numerous state-of-the-art models for vision and language tasks (e.g., GPT, LLaVa), is an important problem machine learning. One recent effective strategy to merge token representations within models, aiming reduce computational memory requirements while maintaining accuracy. Prior works have proposed algorithms based on Bipartite Soft Matching (BSM), which divides tokens into distinct sets merges top k...
Abstract Japanese encephalitis (JE) is a mosquito-borne disease, known for its high death and disability rate among symptomatic cases. Many effective vaccines are available JE, the use of recently developed inexpensive vaccine has been increasing over recent years particularly with Gavi support. Estimates local burden past impact vaccination therefore increasingly needed, but difficult due to limitations JE surveillance. In this study, we implemented mathematical modelling method combined...