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Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Qi Cao, Jianwen Tao, Yufang Dan, Di Zhou • Scientific Reports (2026)

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-44991-7

On the practical aspects of machine learning based active power loss forecasting in transmission networks

Franko Pandžić, Ivan Sudić, Tomislav Capuder, Ivan Pavičić • IET Generation, Transmission & Distribution (2024)

Abstract The cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecast...

DOAJ Open Access (DOAJ) DOI: 10.1049/gtd2.13205