Buchumschlag

SHAP-Integrated Convolutional Diagnostic Networks for Feature-Selective Medical Analysis

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Hu, Yan, Chaddad, Ahmad
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

FACMIC: Federated Adaptative CLIP Model for Medical Image Classification
von: Wu, Yihang, et al.
Veröffentlicht: (2024)

Analysis of Convolutional Neural Network-based Image Classifications: A Multi-Featured Application for Rice Leaf Disease Prediction and Recommendations for Farmers
von: Paneru, Biplov, et al.
Veröffentlicht: (2024)

Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI
von: Ahmed, Maryam, et al.
Veröffentlicht: (2024)

Disease Classification and Impact of Pretrained Deep Convolution Neural Networks on Diverse Medical Imaging Datasets across Imaging Modalities
von: Borah, Jutika, et al.
Veröffentlicht: (2024)

Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Images
von: Okonoda, Michael, et al.
Veröffentlicht: (2026)

Automatic Image Colorization with Convolutional Neural Networks and Generative Adversarial Networks
von: Qiu, Changyuan, et al.
Veröffentlicht: (2025)

On-chip Hyperspectral Image Segmentation with Fully Convolutional Networks for Scene Understanding in Autonomous Driving
von: Gutiérrez-Zaballa, Jon, et al.
Veröffentlicht: (2024)

Multi-Label Classification of Thoracic Diseases using Dense Convolutional Network on Chest Radiographs
von: Bhusal, Dipkamal, et al.
Veröffentlicht: (2022)

A Deep Convolutional Neural Network-Based Novel Class Balancing for Imbalance Data Segmentation
von: Kalsoom, Atifa, et al.
Veröffentlicht: (2025)

Exploring Fully Convolutional Networks for the Segmentation of Hyperspectral Imaging Applied to Advanced Driver Assistance Systems
von: Gutiérrez-Zaballa, Jon, et al.
Veröffentlicht: (2024)

Yucca: A Deep Learning Framework For Medical Image Analysis
von: Llambias, Sebastian Nørgaard, et al.
Veröffentlicht: (2024)

A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network
von: Díaz-Pernas, Francisco Javier, et al.
Veröffentlicht: (2024)

Revolutionizing Disease Diagnosis with simultaneous functional PET/MR and Deeply Integrated Brain Metabolic, Hemodynamic, and Perfusion Networks
von: Wang, Luoyu, et al.
Veröffentlicht: (2024)

RAPNet: A Receptive-Field Adaptive Convolutional Neural Network for Pansharpening
von: Tang, Tao, et al.
Veröffentlicht: (2025)

FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification
von: Sengupta, Prajit, et al.
Veröffentlicht: (2025)

ChiNet: Deep Recurrent Convolutional Learning for Multimodal Spacecraft Pose Estimation
von: Rondao, Duarte, et al.
Veröffentlicht: (2021)

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound
von: Wang, Yi, et al.
Veröffentlicht: (2019)

Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring
von: Dang, Khoi Tran, et al.
Veröffentlicht: (2024)

Analysing Diffusion Segmentation for Medical Images
von: Öttl, Mathias, et al.
Veröffentlicht: (2024)

Robust Training with Data Augmentation for Medical Imaging Classification
von: Martínez-Martínez, Josué, et al.
Veröffentlicht: (2025)

HYDEN: Hyperbolic Density Representations for Medical Images and Reports
von: Qiao, Zhi, et al.
Veröffentlicht: (2024)

MIND: A Noise-Adaptive Denoising Framework for Medical Images Integrating Multi-Scale Transformer
von: Tang, Tao, et al.
Veröffentlicht: (2025)

Enhancing Diagnostic in 3D COVID-19 Pneumonia CT-scans through Explainable Uncertainty Bayesian Quantification
von: Fierro, Juan Manuel Liscano, et al.
Veröffentlicht: (2025)

An Enhanced Classification Method Based on Adaptive Multi-Scale Fusion for Long-tailed Multispectral Point Clouds
von: Liu, TianZhu, et al.
Veröffentlicht: (2024)

Few-Shot Multimodal Medical Imaging: A Theoretical Framework
von: Mohsin, Md Talha, et al.
Veröffentlicht: (2025)

BubbleID: A Deep Learning Framework for Bubble Interface Dynamics Analysis
von: Dunlap, Christy, et al.
Veröffentlicht: (2024)

Features Fusion for Dual-View Mammography Mass Detection
von: Varlamova, Arina, et al.
Veröffentlicht: (2024)

Interpretable Deep Learning Framework for Improved Disease Classification in Medical Imaging
von: Borah, Jutika, et al.
Veröffentlicht: (2025)

Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection
von: He, Weijie, et al.
Veröffentlicht: (2024)

Experience with Single Domain Generalization in Real World Medical Imaging Deployments
von: Banerjee, Ayan, et al.
Veröffentlicht: (2026)

Towards Ground-truth-free Evaluation of Any Segmentation in Medical Images
von: Senbi, Ahjol, et al.
Veröffentlicht: (2024)

Distributional Drift Detection in Medical Imaging with Sketching and Fine-Tuned Transformer
von: Wu, Yusen, et al.
Veröffentlicht: (2024)

MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification
von: Sibhai, Mohammed Maaz, et al.
Veröffentlicht: (2026)

MedCondDiff: Lightweight, Robust, Semantically Guided Diffusion for Medical Image Segmentation
von: Huang, Ruirui, et al.
Veröffentlicht: (2025)

A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation
von: Biswas, Koushik, et al.
Veröffentlicht: (2024)

U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities
von: Neha, Fnu, et al.
Veröffentlicht: (2024)

Research on Deep Learning Model of Feature Extraction Based on Convolutional Neural Network
von: Liu, Houze, et al.
Veröffentlicht: (2024)

Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation
von: Shakarami, Ashkan, et al.
Veröffentlicht: (2025)

Boosting Vision Semantic Density with Anatomy Normality Modeling for Medical Vision-language Pre-training
von: Cao, Weiwei, et al.
Veröffentlicht: (2025)

Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST
von: Wu, Fuping, et al.
Veröffentlicht: (2025)