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This research involving human participants complies with all relevant ethical regulations, including obtaining informed consent from all participants through the recruitment sites. Ethical review and ...

When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill. Researchers at MIT, the ...

Deep learning algorithms for ultra-widefield fundus photos can identify retinal detachments with precision, supporting early diagnoses in varied settings. Deep learning (DL) models applied to ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

Research indicates that repetition and distributed practice effectively fires and rewires the brain, thereby strengthening memory and improving learning potential. This approach aims to develop and ...

ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...

We are currently training with the following code: yolov8Det = trainYOLOv8ObjectDetector('data.yaml', 'yolov8n.pt', ImageSize=[720 720 3], MaxEpochs=10); The structure of yolov8n.pt that we are using ...

Google DeepMind is rolling out Gemini 2.5 Deep Think, which, the company says, is its most advanced AI reasoning model, able to answer questions by exploring and considering multiple ideas ...

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...