COVID-19

Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision

Structural integrity is vital for maintaining the safety and longevity of concrete infrastructures such as bridges, tunnels, and walls. Traditional methods for detecting damages like cracks and spalls are labor-intensive, time-consuming, and prone to human error. To address these challenges, this study explores advanced data-driven techniques using deep learning for automated damage detection an...

CatV2TON: Taming Diffusion Transformers for Vision-Based Virtual Try-On with Temporal Concatenation

Virtual try-on (VTON) technology has gained attention due to its potential to transform online retail by enabling realistic clothing visualization of images and videos. However, most existing methods struggle to achieve high-quality results across image and video try-on tasks, especially in long video scenarios. In this work, we introduce CatV2TON, a simple and effective vision-based virtual try...

GAUDA: Generative Adaptive Uncertainty-guided Diffusion-based Augmentation for Surgical Segmentation

Augmentation by generative modelling yields a promising alternative to the accumulation of surgical data, where ethical, organisational and regulato...

Enhancing Diagnostic in 3D COVID-19 Pneumonia CT-scans through Explainable Uncertainty Bayesian Quantification

Accurately classifying COVID-19 pneumonia in 3D CT scans remains a significant challenge in the field of medical image analysis. Although determinis...

Physics-informed DeepCT: Sinogram Wavelet Decomposition Meets Masked Diffusion

Diffusion model shows remarkable potential on sparse-view computed tomography (SVCT) reconstruction. However, when a network is trained on a limited...

Generalized Single-Image-Based Morphing Attack Detection Using Deep Representations from Vision Transformer

Face morphing attacks have posed severe threats to Face Recognition Systems (FRS), which are operated in border control and passport issuance use ca...

Double Visual Defense: Adversarial Pre-training and Instruction Tuning for Improving Vision-Language Model Robustness

This paper investigates the robustness of vision-language models against adversarial visual perturbations and introduces a novel ``double visual def...

ThinTact:Thin Vision-Based Tactile Sensor by Lensless Imaging

Vision-based tactile sensors have drawn increasing interest in the robotics community. However, traditional lens-based designs impose minimum thickn...

Interpretable Droplet Digital PCR Assay for Trustworthy Molecular Diagnostics

Accurate molecular quantification is essential for advancing research and diagnostics in fields such as infectious diseases, cancer biology, and gen...

Cancer-Net PCa-Seg: Benchmarking Deep Learning Models for Prostate Cancer Segmentation Using Synthetic Correlated Diffusion Imaging

Prostate cancer (PCa) is the most prevalent cancer among men in the United States, accounting for nearly 300,000 cases, 29% of all diagnoses and 35,...

Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation

Small object segmentation, like tumor segmentation, is a difficult and critical task in the field of medical image analysis. Although deep learning ...

SimGen: A Diffusion-Based Framework for Simultaneous Surgical Image and Segmentation Mask Generation

Acquiring and annotating surgical data is often resource-intensive, ethical constraining, and requiring significant expert involvement. While genera...

Uncovering Bias in Foundation Models: Impact, Testing, Harm, and Mitigation

Bias in Foundation Models (FMs) - trained on vast datasets spanning societal and historical knowledge - poses significant challenges for fairness an...

RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation

In recent years, there have been significant advancements in deep learning for medical image analysis, especially with convolutional neural networks...

Benchmarking Graph Representations and Graph Neural Networks for Multivariate Time Series Classification

Multivariate Time Series Classification (MTSC) enables the analysis if complex temporal data, and thus serves as a cornerstone in various real-world...

SmartEraser: Remove Anything from Images using Masked-Region Guidance

Object removal has so far been dominated by the mask-and-inpaint paradigm, where the masked region is excluded from the input, leaving models relyin...

A Feature-Level Ensemble Model for COVID-19 Identification in CXR Images using Choquet Integral and Differential Evolution Optimization

The COVID-19 pandemic has profoundly impacted billions globally. It challenges public health and healthcare systems due to its rapid spread and seve...

An Intra- and Cross-frame Topological Consistency Scheme for Semi-supervised Atherosclerotic Coronary Plaque Segmentation

Enhancing the precision of segmenting coronary atherosclerotic plaques from CT Angiography (CTA) images is pivotal for advanced Coronary Atheroscler...

AlgoRxplorers | Precision in Mutation: Enhancing Drug Design with Advanced Protein Stability Prediction Tools

Predicting the impact of single-point amino acid mutations on protein stability is essential for understanding disease mechanisms and advancing drug...

LarvSeg: Exploring Image Classification Data For Large Vocabulary Semantic Segmentation via Category-wise Attentive Classifier

Scaling up the vocabulary of semantic segmentation models is extremely challenging because annotating large-scale mask labels is labour-intensive an...