Alternative Medicine

Weakly Supervised Pixel-Level Annotation with Visual Interpretability

Medical image annotation is essential for diagnosing diseases, yet manual annotation is time-consuming, costly, and prone to variability among experts. To address these challenges, we propose an automated explainable annotation system that integrates ensemble learning, visual explainability, and uncertainty quantification. Our approach combines three pre-trained deep learning models - ResNet50, ...

Reliable Explainability of Deep Learning Spatial-Spectral Classifiers for Improved Semantic Segmentation in Autonomous Driving

Integrating hyperspectral imagery (HSI) with deep neural networks (DNNs) can strengthen the accuracy of intelligent vision systems by combining spectral and spatial information, which is useful for tasks like semantic segmentation in autonomous driving. To advance research in such safety-critical systems, determining the precise contribution of spectral information to complex DNNs' output is nee...

Spatial and Frequency Domain Adaptive Fusion Network for Image Deblurring

Image deblurring aims to reconstruct a latent sharp image from its corresponding blurred one. Although existing methods have achieved good performan...

Mentoring Software in Education and Its Impact on Teacher Development: An Integrative Literature Review

Mentoring software is a pivotal innovation in addressing critical challenges in teacher development within educational institutions. This study expl...

RT-DEMT: A hybrid real-time acupoint detection model combining mamba and transformer

Traditional Chinese acupuncture methods often face controversy in clinical practice due to their high subjectivity. Additionally, current intelligen...

E2LVLM:Evidence-Enhanced Large Vision-Language Model for Multimodal Out-of-Context Misinformation Detection

Recent studies in Large Vision-Language Models (LVLMs) have demonstrated impressive advancements in multimodal Out-of-Context (OOC) misinformation d...

Multi-Scale Transformer Architecture for Accurate Medical Image Classification

This study introduces an AI-driven skin lesion classification algorithm built on an enhanced Transformer architecture, addressing the challenges of ...

xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods

The growing complexity of machine learning and deep learning models has led to an increased reliance on opaque "black box" systems, making it diffic...

A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis

Resting-state functional magnetic resonance imaging (rs-fMRI) and its derived functional connectivity networks (FCNs) have become critical for under...

Fruit Fly Classification (Diptera: Tephritidae) in Images, Applying Transfer Learning

This study develops a transfer learning model for the automated classification of two species of fruit flies, Anastrepha fraterculus and Ceratitis c...

Complementary Subspace Low-Rank Adaptation of Vision-Language Models for Few-Shot Classification

Vision language model (VLM) has been designed for large scale image-text alignment as a pretrained foundation model. For downstream few shot classif...

Mitigating GenAI-powered Evidence Pollution for Out-of-Context Multimodal Misinformation Detection

While large generative artificial intelligence (GenAI) models have achieved significant success, they also raise growing concerns about online infor...

Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays

Chest X-rays play a pivotal role in diagnosing respiratory diseases such as pneumonia, tuberculosis, and COVID-19, which are prevalent and present u...

Multimodal AI on Wound Images and Clinical Notes for Home Patient Referral

Chronic wounds affect 8.5 million Americans, particularly the elderly and patients with diabetes. These wounds can take up to nine months to heal, m...

EVolutionary Independent DEtermiNistiC Explanation

The widespread use of artificial intelligence deep neural networks in fields such as medicine and engineering necessitates understanding their decis...

Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation

Class activation map (CAM) has been widely used to highlight image regions that contribute to class predictions. Despite its simplicity and computat...

Detection of Vascular Leukoencephalopathy in CT Images

Artificial intelligence (AI) has seen a significant surge in popularity, particularly in its application to medicine. This study explores AI's role ...

Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis

We present a simple approach to make pre-trained Vision Transformers (ViTs) interpretable for fine-grained analysis, aiming to identify and localize...

Revolutionizing Communication with Deep Learning and XAI for Enhanced Arabic Sign Language Recognition

This study introduces an integrated approach to recognizing Arabic Sign Language (ArSL) using state-of-the-art deep learning models such as MobileNe...

Explainable AI-Enhanced Deep Learning for Pumpkin Leaf Disease Detection: A Comparative Analysis of CNN Architectures

Pumpkin leaf diseases are significant threats to agricultural productivity, requiring a timely and precise diagnosis for effective management. Tradi...