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PSO-optimized fractional order CNNs revolutionize breast cancer detection with 99.35% accuracy, superior sensitivity, and robust image analysi
PSO-Optimized Fractional Order CNNs for Enhanced Breast Cancer Detection
Early Detection, Smarter AI: How PSO-Optimized Fractional Order CNNs Are Transforming Breast Cancer Diagnosis Every year, millions of women face the daunting...
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Visual representation of AMGF-GNN framework for tumor grading using multi-graph fusion in histopathology.
AMGF-GNN: Adaptive Multi-Graph Fusion for Tumor Grading in Pathology Images
In the rapidly evolving field of computational pathology, accurate tumor grading in pathology images remains a cornerstone for effective cancer diagnosis...
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Anchor-Based Knowledge Distillation (AKD), a breakthrough in trustworthy AI for efficient model compression.
Anchor-Based Knowledge Distillation: A Trustworthy AI Approach for Efficient Model Compression
In the rapidly evolving field of artificial intelligence (AI), knowledge distillation (KD) has emerged as a cornerstone technique for compressing powerful,...
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Diagram of the BiMT-TCN model architecture showing BiLSTM, modified Transformer, and TCN layers for enhanced stock forecasting.
BiMT-TCN: Revolutionizing Stock Price Prediction with Hybrid Deep Learning
In the fast-paced world of financial markets, accurate stock price prediction has long been the holy grail for investors, analysts, and AI researchers....
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ProMSC-MIS: a revolutionary prompt-based multimodal semantic communication system for multi-spectral image segmentation.
ProMSC-MIS: Revolutionizing Multimodal Semantic Communication for Multi-Spectral Image Segmentation
In the rapidly evolving landscape of artificial intelligence and wireless communication, a groundbreaking new framework—ProMSC-MIS (Prompt-based Multimodal...
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Illustration of a hybrid AI system linking microscope images of metal microstructures with expert textual assessments using vision-language models like CLIP, vision-language representations and FLAVA.
Customized Vision-Language Representations for Industrial Qualification: Bridging AI and Expert Knowledge in Additive Manufacturing
In the rapidly evolving world of additive manufacturing (AM), ensuring the quality and reliability of engineered materials is a critical bottleneck. Traditional...
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CMFDNet architecture for automated polyp segmentation using Cross-Mamba Decoder and Feature Discovery Module
CMFDNet: Revolutionizing Polyp Segmentation with Cross-Mamba and Feature Discovery
Colorectal cancer (CRC) remains one of the most prevalent and deadly cancers worldwide, with early detection playing a pivotal role in reducing mortality....
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AI-generated segmentation of a breast ultrasound image with overlay uncertainty heatmap showing high confidence (blue) and low confidence (yellow) regions near tumor boundaries for breast tumor segmentation.
Towards Trustworthy Breast Tumor Segmentation in Ultrasound Using AI Uncertainty
Breast cancer remains the most diagnosed cancer among women globally, accounting for nearly 1 in 4 cancer cases. Early detection and precise diagnosis...
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GREP model for cell classification
Revolutionizing Digital Pathology: A Deep Dive into GrEp for Superior Epithelial Cell Classification
The field of digital pathology is undergoing a transformation, with deep learning and artificial intelligence unlocking unprecedented opportunities for...
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Diagram showing REM (Routing Entropy Minimization) applied to a Capsule Network, reducing unnecessary parse trees and focusing only on relevant object parts.
Capsule Networks Do Not Need to Model Everything: How REM Reduces Entropy for Smarter AI
In the fast-evolving world of deep learning, capsule networks (CapsNets) have emerged as a promising alternative to traditional convolutional neural networks...
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Illustration of probabilistic smooth attention in a deep learning model for medical image classification, showing uncertainty maps and attention heatmaps over patches of a whole slide image and CT scan slices.
Probabilistic Smooth Attention for Deep Multiple Instance Learning in Medical Imaging
Unlocking Precision in Medical AI: Probabilistic Smooth Attention for Deep Multiple Instance Learning In the rapidly evolving field of medical imaging,...
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Visual explanation of Knowledge Distillation and Feature Map Visualization (KD-FMV) in medical AI models using CNNs for brain tumor, eye disease, and Alzheimer’s classification.
A Knowledge Distillation-Based Approach to Enhance Transparency of Classifier Models
Artificial Intelligence (AI) has revolutionized healthcare, particularly in medical image analysis. However, the “black-box” nature of deep...
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Illustration of the ConvAttenMixer model architecture showing MRI input, convolutional layers, self-attention, external attention, and classification output for brain tumor detection.
ConvAttenMixer: Revolutionizing Brain Tumor Detection with Convolutional Mixer and Attention Mechanisms
In the rapidly advancing field of medical imaging and artificial intelligence (AI), brain tumor detection and classification remain among the most critical...
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Diagram showing DiffAug framework: text-guided diffusion model generating synthetic polyps on colonoscopy images with latent-space validation for medical image segmentation.
Diffusion-Based Data Augmentation for Medical Image Segmentation
In the rapidly evolving field of medical imaging, diffusion-based data augmentation for medical image segmentation is emerging as a game-changing solution...
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ISALUX: A cutting-edge transformer model for low-light image enhancement using illumination and semantic awareness
ISALUX: Revolutionizing Low-Light Image Enhancement with Illumination and Semantics-Aware Transformers
In the world of digital imaging, capturing clear, vibrant photos in low-light conditions has always been a challenge. From dimly lit cityscapes to indoor...
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Illustration of VRM framework showing virtual relation matching between teacher and student models in knowledge distillation.
VRM: Knowledge Distillation via Virtual Relation Matching – A Breakthrough in Model Compression
In the rapidly evolving field of deep learning, knowledge distillation (KD) has emerged as a vital technique for transferring intelligence from large,...
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Framework of the proposed ProMSC-MIS
Prompt-based Multimodal Semantic Communication (ProMSC-MIS) for Multi-spectral Image Segmentation
In the rapidly evolving landscape of AI-driven wireless communication, prompt-based multimodal semantic communication is emerging as a game-changer—especially...
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Self-Knowledge Distillation (Self-KD) enhances vision-audio capability in Omnimodal Large Language Models (OLLMs)
Enhancing Vision-Audio Capability in Omnimodal LLMs with Self-KD
Introduction: The Challenge of Audio-Vision Integration in Omnimodal LLMs Omnimodal Large Language Models (OLLMs) like GPT-4o and Megrez have revolutionized...
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