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J.H.G. Dauwels

47 records found

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 ...
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 ...

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 ...
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 ...
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 ...

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 ...

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 ...
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 ...
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 ...

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, ...
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 ...
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 ...

MERLIon CCS Challenge

A English-Mandarin code-switching child-directed speech corpus for language identification and diarization

To enhance the reliability and robustness of language identification (LID) and language diarization (LD) systems for heterogeneous populations and scenarios, there is a need for speech processing models to be trained on datasets that feature diverse language registers and speech ...

PEM

Perception Error Model for Virtual Testing of Autonomous Vehicles

Even though virtual testing of Autonomous Vehicles (AVs) has been well recognized as essential for safety assessment, AV simulators are still undergoing active development. One particular challenge is the problem of including the Sensing and Perception (S&P) subsystem into th ...

Slot-VAE

Object-Centric Scene Generation with Slot Attention

Slot attention has shown remarkable object-centric representation learning performance in computer vision tasks without requiring any supervision. Despite its object-centric binding ability brought by compositional modelling, as a deterministic module, slot attention lacks the ab ...
Language development experts need tools that can automatically identify languages from fluent, conversational speech and provide reliable estimates of usage rates at the level of an individual recording. However, LID systems are typically evaluated on metrics such as equal error ...
Global climate models are susceptible to drift, causing spurious trends in output variables. Drift is often corrected using data from a control simulation. However, internal climate variability within the control simulation introduces uncertainty to the drift correction process. ...
Autonomous vehicles (AV) are one of the greatest technological advancements of this decade and a giant leap in the transportation industry and mobile robotics. Autonomous vehicles face several major challenges in achieving higher levels of autonomy. One of these is to find a fast ...