Ophthalmology

GMAR: Gradient-Driven Multi-Head Attention Rollout for Vision Transformer Interpretability

The Vision Transformer (ViT) has made significant advancements in computer vision, utilizing self-attention mechanisms to achieve state-of-the-art performance across various tasks, including image classification, object detection, and segmentation. Its architectural flexibility and capabilities have made it a preferred choice among researchers and practitioners. However, the intricate multi-head...

Low-Rank Adaptive Structural Priors for Generalizable Diabetic Retinopathy Grading

Diabetic retinopathy (DR), a serious ocular complication of diabetes, is one of the primary causes of vision loss among retinal vascular diseases. Deep learning methods have been extensively applied in the grading of diabetic retinopathy (DR). However, their performance declines significantly when applied to data outside the training distribution due to domain shifts. Domain generalization (DG) ...

VIST-GPT: Ushering in the Era of Visual Storytelling with LLMs?

Visual storytelling is an interdisciplinary field combining computer vision and natural language processing to generate cohesive narratives from seq...

Boosting Single-domain Generalized Object Detection via Vision-Language Knowledge Interaction

Single-Domain Generalized Object Detection~(S-DGOD) aims to train an object detector on a single source domain while generalizing well to diverse un...

Uncovering potential effects of spontaneous waves on synaptic development: the visual system as a model

Spontaneous waves are ubiquitous during early brain development and are hypothesized to drive the development of receptive fields (RFs). Different s...

MediAug: Exploring Visual Augmentation in Medical Imaging

Data augmentation is essential in medical imaging for improving classification accuracy, lesion detection, and organ segmentation under limited data...

Surgeons vs. Computer Vision: A comparative analysis on surgical phase recognition capabilities

Purpose: Automated Surgical Phase Recognition (SPR) uses Artificial Intelligence (AI) to segment the surgical workflow into its key events, function...

Revisiting Transformers through the Lens of Low Entropy and Dynamic Sparsity

Compression has been a critical lens to understand the success of Transformers. In the past, we have typically taken the target distribution as a cr...

Proof-of-TBI -- Fine-Tuned Vision Language Model Consortium and OpenAI-o3 Reasoning LLM-Based Medical Diagnosis Support System for Mild Traumatic Brain Injury (TBI) Prediction

Mild Traumatic Brain Injury (TBI) detection presents significant challenges due to the subtle and often ambiguous presentation of symptoms in medica...

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models

Deep neural networks (DNNs) have proven to be successful in various computer vision applications such that models even infer in safety-critical situ...

Revisiting Data Auditing in Large Vision-Language Models

With the surge of large language models (LLMs), Large Vision-Language Models (VLMs)--which integrate vision encoders with LLMs for accurate visual g...

Exhaled Breath Analysis Through the Lens of Molecular Communication: A Survey

Molecular Communication (MC) has long been envisioned to enable an Internet of Bio-Nano Things (IoBNT) with medical applications, where nanomachines...

Multi-Grained Compositional Visual Clue Learning for Image Intent Recognition

In an era where social media platforms abound, individuals frequently share images that offer insights into their intents and interests, impacting i...

E-InMeMo: Enhanced Prompting for Visual In-Context Learning

Large-scale models trained on extensive datasets have become the standard due to their strong generalizability across diverse tasks. In-context lear...

A BERT-Style Self-Supervised Learning CNN for Disease Identification from Retinal Images

In the field of medical imaging, the advent of deep learning, especially the application of convolutional neural networks (CNNs) has revolutionized ...

DMS-Net:Dual-Modal Multi-Scale Siamese Network for Binocular Fundus Image Classification

Ophthalmic diseases pose a significant global health challenge, yet traditional diagnosis methods and existing single-eye deep learning approaches o...

Back to Fundamentals: Low-Level Visual Features Guided Progressive Token Pruning

Vision Transformers (ViTs) excel in semantic segmentation but demand significant computation, posing challenges for deployment on resource-constrain...

Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency

Recent advancements in Large Vision-Language Models (LVLMs) have significantly enhanced their ability to integrate visual and linguistic information...

Revisiting Reset Mechanisms in Spiking Neural Networks for Sequential Modeling: Specialized Discretization for Binary Activated RNN

In the field of image recognition, spiking neural networks (SNNs) have achieved performance comparable to conventional artificial neural networks (A...

Revisiting Reset Mechanisms in Spiking Neural Networks for Sequential Modeling: Specialized Discretization for Binary Activated RNN

In the field of image recognition, spiking neural networks (SNNs) have achieved performance comparable to conventional artificial neural networks (A...