Ophthalmology

Deep Learning for Detection of Corneal Perforation on Anterior Segment Optical Coherence Tomography in Microbial Keratitis

Purpose: To develop and evaluate deep learning models for automated detection of corneal perforation in microbial keratitis using anterior segment optical coherence tomography (ASOCT) images. Methods: We enrolled 150 patients with microbiologically confirmed keratitis. Contralateral healthy eyes served as controls. Four convolutional neural network models using ResNet architecture were trained and...

H2VLR: Heterogeneous Hypergraph Vision-Language Reasoning for Few-Shot Anomaly Detection

As a classic vision task, anomaly detection has been widely applied in industrial inspection and medical imaging. In this task, data scarcity is often a frequently-faced issue. To solve it, the few-shot anomaly detection (FSAD) scheme is attracting increasing attention. In recent years, beyond traditional visual paradigm, Vision-Language Model (VLM) has been extensively explored to boost this fiel...

MetaDent: Labeling Clinical Images for Vision-Language Models in Dentistry

Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remain...

UniDoc-RL: Coarse-to-Fine Visual RAG with Hierarchical Actions and Dense Rewards

Retrieval-Augmented Generation (RAG) extends Large Vision-Language Models (LVLMs) with external visual knowledge. However, existing visual RAG systems...

VisPCO: Visual Token Pruning Configuration Optimization via Budget-Aware Pareto-Frontier Learning for Vision-Language Models

Visual token pruning methods effectively mitigate the quadratic computational growth caused by processing high-resolution images and video frames in v...

AI Powered Image Analysis for Phishing Detection

Phishing websites now rely heavily on visual imitation-copied logos, similar layouts, and matching colours-to avoid detection by text- and URL-based s...

UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing

Ultra-high-resolution (UHR) remote sensing imagery couples kilometer-scale context with query-critical evidence that may occupy only a few pixels. Suc...

HINTBench: Horizon-agent Intrinsic Non-attack Trajectory Benchmark

Existing agent-safety evaluation has focused mainly on externally induced risks. Yet agents may still enter unsafe trajectories under benign condition...

Reward Design for Physical Reasoning in Vision-Language Models

Physical reasoning over visual inputs demands tight integration of visual perception, domain knowledge, and multi-step symbolic inference. Yet even st...

Reading Between the Pixels: Linking Text-Image Embedding Alignment to Typographic Attack Success on Vision-Language Models

We study typographic prompt injection attacks on vision-language models (VLMs), where adversarial text is rendered as images to bypass safety mechanis...

Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration

Automated diagnosis based on color fundus photography is essential for large-scale glaucoma screening. However, existing deep learning models are typi...

Reading Between the Pixels: Linking Text-Image Embedding Alignment to Typographic Attack Success on Vision-Language Models

We study typographic prompt injection attacks on vision-language models (VLMs), where adversarial text is rendered as images to bypass safety mechanis...

Task Alignment: A simple and effective proxy for model merging in computer vision

Efficiently merging several models fine-tuned for different tasks, but stemming from the same pretrained base model, is of great practical interest. D...

Boosting Visual Instruction Tuning with Self-Supervised Guidance

Multimodal large language models (MLLMs) perform well on many vision-language tasks but often struggle with vision-centric problems that require fine-...

Ultra-low-light computer vision using trained photon correlations

Illumination using correlated photon sources has been established as an approach to allowing high-fidelity images to be reconstructed from noisy camer...

TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment

Recent progress in vision-language pretraining has enabled significant improvements to many downstream computer vision applications, such as classific...

Scene Change Detection with Vision-Language Representation Learning

Scene change detection (SCD) is crucial for urban monitoring and navigation but remains challenging in real-world environments due to lighting variati...

Anthropogenic Regional Adaptation in Multimodal Vision-Language Model

While the field of vision-language (VL) has achieved remarkable success in integrating visual and textual information across multiple languages and do...

SVD-Prune: Training-Free Token Pruning For Efficient Vision-Language Models

Vision-Language Models (VLM) have revolutionized multimodal learning by jointly processing visual and textual information. Yet, they face significant ...

CLAY: Conditional Visual Similarity Modulation in Vision-Language Embedding Space

Human perception of visual similarity is inherently adaptive and subjective, depending on the users' interests and focus. However, most image retrieva...