Abstract: Monitoring sea ice in polar regions is essential for environmental modeling and ship navigation. National ice agencies expect robust sea ice classification methods for operational use.

Amplifying words and ideas to separate the ordinary from the extraordinary, making the mundane majestic. Amplifying words and ideas to separate the ordinary from the ...

To evaluate the diagnostic performance of semi-supervised learning models for aggressive prostate cancer detection on MRI compared to fully supervised models trained with additional expert annotations ...

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...

Semi-supervised learning (SSL) aims to improve performance by exploiting unlabeled data when labels are scarce. Conventional SSL studies typically assume close environments where important factors ...

We investigate the failures of representative semi-supervised learning methods, e.g., FixMatch and DebiasPL, in the challenging few-shot setup for finetuning a pretrained VLM. Our analyses reveal the ...

TraPO is a semi-supervised reinforcement learning framework that bridges unlabeled and labeled samples for training large reasoning models (LRMs). Built upon GRPO, TraPO leverages a small set of ...

Decoding emotional states from electroencephalography (EEG) signals is a fundamental goal in affective neuroscience. This endeavor requires accurately modeling the complex spatio-temporal dynamics of ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Brain-computer interfaces (BCIs) are advanced and innovative systems that enable direct communication between humans and external devices by utilizing data encoded in the brain activity (Shi et al., ...