IEEE

Data-Efficient Object Detection on Construction Sites Using Reweighting Mechanism and Cross-Batch Contrastive Learning

Abstract: Deep learning-based object detectors face unique challenges in construction sites, including severe occlusions from complex spatial arrangements, similar appearances between different ...
IEEE

Single-Domain Generalized Object Detection With Frequency Whitening and Contrastive Learning

Abstract: Single-Domain Generalization Object Detection (Single-DGOD) refers to training a model with only one source domain, enabling the model to generalize to any unseen domain. For instance, a ...
GitHub

Real-Time Object Detection Meets DINOv3

DEIMv2 is an evolution of the DEIM framework while leveraging the rich features from DINOv3. Our method is designed with various model sizes, from an ultra-light version up to S, M, L, and X, to be ...
Frontiers

An interpretable machine learning model for predicting sepsis risk in ICU patients with non-traumatic subarachnoid hemorrhage: development and validation using the MIMIC-IV ...

1 Graduate School of Xinxiang Medical University, Xinxiang, China 2 Department of Neurosurgical Intensive Care Unit, Henan Provincial People’s Hospital, Zhengzhou, China Objective: This study aimed to ...
Reuters

Bristol Myers partners with Microsoft for AI-driven lung cancer detection

Jan 20 (Reuters) - Bristol Myers Squibb (BMY.N), opens new tab said on Tuesday it had signed an agreement with Microsoft (MSFT.O), opens new tab to use the tech company's AI-enabled radiology platform ...
Frontiers

A machine learning model for prediction of cardiac arrest-associated acute kidney injury in the ICU: an internal and external validation study

Background: Cardiac arrest-associated acute kidney injury is common after cardiac arrest and adversely affects patient survival and disease outcomes. Early prediction of acute kidney injury is ...