The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
Abstract: Hybrid models that combine convolution and self attention are popular for efficient local feature extraction and capturing long-range dependencies. However, these models often:1) only ...
FairML Datasets provides tools and interfaces to download, load, transform, and analyze the datasets in the FairGround corpus. It handles sensitive attributes and facilitates fairness-aware machine ...
Binary cross-entropy (BCE) is the default loss function for binary classification—but it breaks down badly on imbalanced datasets. The reason is subtle but important: BCE weighs mistakes from both ...
Version of Record: This is the final version of the article. The paper by Xie et al. investigates the micro-evolutionary dynamics of sex-biased gene expression across somatic and gonadal tissues in ...
Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...
This thesis focuses on leveraging Image Processing, Computer Vision, Machine Learning, and Deep Learning, particularly the Vision Transformer (ViT) model, for early identification of Alzheimer’s ...
Abstract: Deep learning-based hyperspectral image (HSI) classification models typically utilize multiple feature extraction layers to learn the features of land covers. Nevertheless, they encounter ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results