Cover Image

Optimized Learning for X-Ray Image Classification for Multi-Class Disease Diagnoses with Accelerated Computing Strategies

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Romero, Sebastian A. Cruz, de Jesus, Ivanelyz Rivera, Quinones, Dariana J. Troche, Gallego, Wilson Rivera
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Chest Disease Detection In X-Ray Images Using Deep Learning Classification Method
by: Hazlett, Alanna, et al.
Published: (2025)

Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays
by: Lei, Yiming, et al.
Published: (2025)

Artificially Generated Visual Scanpath Improves Multi-label Thoracic Disease Classification in Chest X-Ray Images
by: Verma, Ashish, et al.
Published: (2025)

Explainable Lung Disease Classification from Chest X-Ray Images Utilizing Deep Learning and XAI
by: Ifty, Tanzina Taher, et al.
Published: (2024)

From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification
by: Kulkarni, Pranav, et al.
Published: (2023)

AttCDCNet: Attention-enhanced Chest Disease Classification using X-Ray Images
by: Khater, Omar Hesham, et al.
Published: (2024)

CBAM-Enhanced DenseNet121 for Multi-Class Chest X-Ray Classification with Grad-CAM Explainability
by: Dey, Utsho Kumar
Published: (2026)

Diagnosing COVID-19 Severity from Chest X-Ray Images Using ViT and CNN Architectures
by: Lara, Luis, et al.
Published: (2025)

AgriMind: An Ensemble Deep Learning Framework for Multi-Class Plant Disease Classification
by: Koli, Salma Hoque Talukdar, et al.
Published: (2026)

Few-Shot Learning Approach on Tuberculosis Classification Based on Chest X-Ray Images
by: Pramana, A. A. G. Yogi, et al.
Published: (2024)

Optimizing Class Distributions for Bias-Aware Multi-Class Learning
by: Felske, Mirco, et al.
Published: (2025)

Fairness Analysis of CLIP-Based Foundation Models for X-Ray Image Classification
by: Sun, Xiangyu, et al.
Published: (2025)

Enhanced Multi-Class Classification of Gastrointestinal Endoscopic Images with Interpretable Deep Learning Model
by: Kamble, Astitva, et al.
Published: (2025)

DGG-XNet: A Hybrid Deep Learning Framework for Multi-Class Brain Disease Classification with Explainable AI
by: Eity, Sumshun Nahar, et al.
Published: (2025)

XDT-CXR: Investigating Cross-Disease Transferability in Zero-Shot Binary Classification of Chest X-Rays
by: Rahman, Umaima, et al.
Published: (2024)

ACIL: Active Class Incremental Learning for Image Classification
by: Bhattacharya, Aditya R., et al.
Published: (2026)

Primitive-Driven Acceleration of Hyperdimensional Computing for Real-Time Image Classification
by: Parikh, Dhruv, et al.
Published: (2026)

Anatomic Feature Fusion Model for Diagnosing Calcified Pulmonary Nodules on Chest X-Ray
by: Choi, Hyeonjin, et al.
Published: (2025)

Few-shot learning for COVID-19 Chest X-Ray Classification with Imbalanced Data: An Inter vs. Intra Domain Study
by: Galán-Cuenca, Alejandro, et al.
Published: (2024)

Ateromatosis en arterias renales de pacientes fallecidos en el Hospital CIMEQ de Ciudad de La Habana, Cuba, 2008
by: Dariana Matamoros Romero
Published: (2010)

MultiFusionNet: Multilayer Multimodal Fusion of Deep Neural Networks for Chest X-Ray Image Classification
by: Agarwal, Saurabh, et al.
Published: (2024)

Multi-Class Unlearning for Image Classification via Weight Filtering
by: Poppi, Samuele, et al.
Published: (2023)

Momentum-Anchored Multi-Scale Fusion Model for Long-Tailed Chest X-Ray Classification
by: Khuong, Duy Hoang, et al.
Published: (2026)

Learning to Obstruct Few-Shot Image Classification over Restricted Classes
by: Zheng, Amber Yijia, et al.
Published: (2024)

Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification
by: Kilickaya, Sertac, et al.
Published: (2023)

Online Class-Incremental Learning For Real-World Food Image Classification
by: Raghavan, Siddeshwar, et al.
Published: (2023)

Addressing Imbalance for Class Incremental Learning in Medical Image Classification
by: Hao, Xuze, et al.
Published: (2024)

Improvement Strategies for Few-Shot Learning in OCT Image Classification of Rare Retinal Diseases
by: Tai, Cheng-Yu, et al.
Published: (2025)

Transformer-based Federated Learning for Multi-Label Remote Sensing Image Classification
by: Büyüktaş, Barış, et al.
Published: (2024)

Multi-OCT-SelfNet: Integrating Self-Supervised Learning with Multi-Source Data Fusion for Enhanced Multi-Class Retinal Disease Classification
by: Jannat, Fatema-E-, et al.
Published: (2024)

One-Class Risk Estimation for One-Class Hyperspectral Image Classification
by: Zhao, Hengwei, et al.
Published: (2022)

RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace
by: Shrestha, Pragyan, et al.
Published: (2024)

UniChest: Conquer-and-Divide Pre-training for Multi-Source Chest X-Ray Classification
by: Dai, Tianjie, et al.
Published: (2023)

Chest X-Rays Image Classification from beta-Variational Autoencoders Latent Features
by: Crespi, Leonardo, et al.
Published: (2021)

EndoCIL: A Class-Incremental Learning Framework for Endoscopic Image Classification
by: Liu, Bingrong, et al.
Published: (2025)

Effective-LDAM: An Effective Loss Function To Mitigate Data Imbalance for Robust Chest X-Ray Disease Classification
by: S, Sree Rama Vamsidhar, et al.
Published: (2024)

Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning
by: Arteaga, Gabriel Y., et al.
Published: (2025)

Loss Design and Architecture Selection for Long-Tailed Multi-Label Chest X-Ray Classification
by: Sulake, Nikhileswara Rao
Published: (2026)

CXR-LT 2026 Challenge: Projection-Aware Multi-Label and Zero-Shot Chest X-Ray Classification
by: Cho, Juno, et al.
Published: (2026)

Class-Conditioned Transformation for Enhanced Robust Image Classification
by: Blau, Tsachi, et al.
Published: (2023)