J.H.G. Dauwels
48 records found
1
Enhancing Autonomous Vehicle Navigation Through Computer Vision
Techniques for Lane Marker Detection and Rain Removal
Autonomous Vehicles (AVs) equipped with camera systems have emerged as a pivotal solution for smart urban mobility. The escalating demand for AVs emphasizes the need to prioritize driving safety, especially in challenging weather conditions like heavy rain. In this context, the a
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Background: Intra-group discussions during actual TBL sessions play a huge role in knowledge consolidation and learning but are often understudied. Aims: Using a pre-registered study framework, we examined if participation equity (H1), reciprocal interaction (H2), information den
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Cardiac output (CO) is a vital hemodynamic parameter that reflects the blood volume pumped by the heart per minute. A less-invasive way to estimate CO is by analyzing arterial blood pressure (ABP) waveforms. However, the relationship between CO and blood pressure is unknown. This
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Nowcasting leverages real-time atmospheric conditions to forecast weather over short periods. State-of-the-art models, including PySTEPS, encounter difficulties in accurately forecasting extreme weather events because of their unpredictable distribution patterns. In this study, w
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Deep learning-based object detectors, while offering exceptional performance, are data-dependent and can suffer from generalization issues. In this work, we investigated deep neural networks for detecting people and medical instruments for the vision-based workflow analysis syste
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MoReSo
A DNN Framework Expediting Content-based Video Image Retrieval (CBVIR)
With the exponential growth of video data, individuals, particularly scholars in the fields of history and sociology, are increasingly reliant on video materials. However, the task of locating specific frames within videos remains a laborious and time-consuming endeavor. Advanced
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Tide–surge interaction plays a substantial role in determining the characteristics of coastal water levels over shallow regions. We study the tide–surge interaction observed at seven tide gauges along Singapore and the east coast of Peninsular Malaysia, focusing on the timing of
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NeuroDots
From Single-Target to Brain-Network Modulation: Why and What Is Needed?
Objectives: Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irres
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Post-induction hypotension (PIH) occurs shortly after anesthesia induction and is related to several post-operative complications. Medications delivered during induction and maintenance of anesthesia are significantly related to PIH occurrence, which remains common due to the int
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Unveiling Hidden Anomalies
A Hybrid Approach for Surface Mounted Electronics
Industrial assembly lines are the heartbeat of modern manufacturing, where precision and efficiency are paramount. This paper introduces a novel hybrid Explainable artificial intelligence (XAI) approach to enhance monitoring and analysis in industrial assembly. By fusing the powe
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LGM3A 2024
The 2nd Workshop on Large Generative Models Meet Multimodal Applications
This workshop aims to explore the potential of large generative models to revolutionize how we interact with multimodal information. A Large Language Model (LLM) represents a sophisticated form of artificial intelligence engineered to comprehend and produce natural language text,
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A probabilistic projection of sea-level rise uses a probability distribution to represent scientific uncertainty. However, alternative probabilistic projections of sea-level rise differ markedly, revealing ambiguity, which poses a challenge to scientific assessment and decision-m
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We propose a manager-worker framework (the implementation of our model is publically available at: https://github.com/zcaicaros/manager-worker-mtsptwr) based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), i.e. multiple
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Nowcasting is an observation-based method that uses the current state of the atmosphere to forecast future weather conditions over several hours. Recent studies have shown the promising potential of using deep learning models for precipitation nowcasting. In this paper, novel dee
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In this paper, we aim to design an automatic camera pose estimation pipeline for clinical spaces such as catheterization laboratories. Our proposed pipeline exploits Scaled-YOLOv4 to detect fixed objects. We adopt the self-supervised key-point detector SuperPoint in combination w
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Data Science Education
The Signal Processing Perspective [SP Education]
In the last decade, the signal processing (SP) community has witnessed a paradigm shift from model-based to data-driven methods. Machine learning (ML) - more specifically, deep learning - methodologies are nowadays widely used in all SP fields, e.g., audio, speech, image, video,
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Functional ultrasound (fUS) is a novel neuroimaging technique that measures brain hemodynamics through a time series of Doppler images. The measured spatiotemporal hemodynamic changes reflect changes in neural activity through the neurovascular coupling (NVC). Often, such image t
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