AI Medical Compendium

Correcting Variable Importance Scored by Random Forests

arXiv Jun 9, 2026

Variable importance produced by Random Forests (RF) is used widely in statistical data analysis, and has played an important role in a variety of tasks such as assisting model interpretation, model selection and diagnosis, and cost-bounded learning e... read more

Methodology cs.LG

Spatially Selective Self-Training for Unsupervised Building Change Detection

arXiv Jun 9, 2026

Unsupervised building change detection aims to learn building-change masks from unlabeled bi-temporal remote sensing images. Existing label-free methods often follow a discrepancy-to-mask paradigm, directly using temporal differences, frozen foundati... read more

Computer Vision and Pattern Recognition

Spatially Selective Self-Training for Unsupervised Building Change Detection

arXiv Jun 9, 2026

Unsupervised building change detection aims to learn building-change masks from unlabeled bi-temporal remote sensing images. Existing label-free methods often follow a discrepancy-to-mask paradigm, directly using temporal differences, frozen foundati... read more

Computer Vision and Pattern Recognition

From Patches to Patients: A study of the tile-to-slide performance transferability in Digital Pathology

arXiv Jun 9, 2026

Foundation Models (FMs) have recently redefined the state-of-the-art in histopathology by providing robust representations for whole-slide image (WSI) analysis. However, selecting the optimal foundation model (FM) for a specific clinical cohort curre... read more

Computer Vision and Pattern Recognition

A Multimodal RGB and Events Dataset for Hand Detection in First-Person View

arXiv Jun 9, 2026

Existing hand detection algorithms work on images and the detection rate is restricted by the frame rate of the camera. In hand detection applications for moving robotic systems, conventional cameras cause motion blur, especially in darker lighting c... read more

Computer Vision and Pattern Recognition

Boosting ECG Classification Performance by Pre-training with Synthesized Data

arXiv Jun 9, 2026

Deep Neural Networks (DNNs) typically require extensive datasets for effective training. In the medical domain, acquiring large-scale data is often challenging due to privacy concerns and the rarity of certain diseases. To address this data scarcity,... read more

Machine Learning cs.AI

Beyond APIs: Probing the Limits of MLLMs in Physical Tool Use

arXiv Jun 9, 2026

Multimodal Large Language Models (MLLMs) excel at utilizing digital APIs and increasingly serve as the "brain" of embodied AI, instructing robots to interact with the physical world. In such embodied settings, a central capability is the use of physi... read more

Computation and Language cs.AI cs.CV

Deep learning for echo sounder data

arXiv Jun 9, 2026

There is no doubt that over the last decade, techniques from the field of machine learning have revolutionized how we process and interpret data, especially images and text. For underwater observations acoustics is a primary source of information, an... read more

Computer Vision and Pattern Recognition

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks

arXiv Jun 9, 2026

RS-MLLMs enable natural-language understanding and spatial reasoning over earth observation imagery. However, existing models support only a narrow range of sensor types and tasks, yielding a fragmented view of the earth and leaving cross-modal geosc... read more

Computer Vision and Pattern Recognition cs.AI

Schmidt Decomposition-Based Methods for Efficient Quantum Image Encoding

arXiv Jun 9, 2026

In quantum image processing, a fundamental step is encoding classical image data into quantum states. This can be achieved using methods such as Flexible Representation of Quantum Images (FRQI), Quantum Probability Image Encoding (QPIE), and Novel En... read more

Computer Vision and Pattern Recognition math.QA quant-ph

Artificial Intelligence Medical Compendium

Correcting Variable Importance Scored by Random Forests

Spatially Selective Self-Training for Unsupervised Building Change Detection

Spatially Selective Self-Training for Unsupervised Building Change Detection

From Patches to Patients: A study of the tile-to-slide performance transferability in Digital Pathology

A Multimodal RGB and Events Dataset for Hand Detection in First-Person View

Boosting ECG Classification Performance by Pre-training with Synthesized Data

Beyond APIs: Probing the Limits of MLLMs in Physical Tool Use

Deep learning for echo sounder data

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks

Schmidt Decomposition-Based Methods for Efficient Quantum Image Encoding

Popular Topics

Recent Journals

Artificial Intelligence Medical Compendium

Stay Ahead of Medical AI

Popular Topics

Recent Journals