MetaMed: Few-shot medical image classification using gradient-based meta-learning

Article Computer Science, Artificial Intelligence

MetaCOVID: A Siamese neural network framework with contrastive loss for n -shot diagnosis of COVID-19 patients

Mohammad Shorfuzzaman et al.

Summary: An AI system based on deep meta learning was proposed to accelerate analysis of chest X-ray (CXR) images for automatic detection of COVID-19 cases. The model integrates contrastive learning and a fine-tuned pre-trained ConvNet encoder to capture unbiased feature representations, achieving 95.6% accuracy and AUC of 0.97 in diagnosing COVID-19 from CXR images.

PATTERN RECOGNITION (2021)

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Article Computer Science, Artificial Intelligence

CoMHisP: A Novel Feature Extractor for Histopathological Image Classification Based on Fuzzy SVM With Within-Class Relative Density

Abhinav Kumar et al.

Summary: This study introduces a novel CoMHisP framework for analyzing cancer histopathological images using a fuzzy support vector machine. Evaluation on a dataset of canine mammary tumor images reveals that the best results were achieved at lower magnifications after stain normalization, with a classification accuracy of 97.25%.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2021)

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Article Automation & Control Systems

Deep Learning in Robotics: Survey on Model Structures and Training Strategies

Artur Istvan Karoly et al.

Summary: This paper proposes a solution by categorizing the major challenges in robotics that leverage deep learning technologies and introducing successful examples to assist in selecting the correct model structure and training strategy.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021)

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Article Computer Science, Information Systems