Meningioma is the most common type of brain tumor. It does not develop in the brain tissue itself, but on the inside of the ...
Mass General Brigham researchers are betting that the next big leap in brain medicine will come from teaching artificial ...
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 ...
The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. The dataset consists of 5-second-long ...
In this study, we developed a dataset of behaviors associated with lameness in dairy cows. The data collection utilized IoT collars that were placed around the necks of 10 dairy cows. This publicly ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
This study presents data on sex differences in gene expression across organs of four mice taxa. The authors have generated a unique and convincing dataset that fills a gap left by previous studies.
This project implements a complete end-to-end pipeline for analyzing RNA-Seq gene expression data to classify different cancer types. Using the PANCAN dataset from UCI Machine Learning Repository, we ...
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 ...
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