Sleep is one of medicine's underused data streams. Clinically, disturbed sleep has often been treated as a symptom of a disorder, but sleep is also a physiological state in which brain, cardiac, ...
Abstract: This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) ...
Abstract: Tabular data is the most prevalent form of structured data, necessitating robust models for classification and regression tasks. Traditional models like eXtreme Gradient Boosting (XGBoost) ...
Deep learning algorithms for ultra-widefield fundus photos can identify retinal detachments with precision, supporting early diagnoses in varied settings. Deep learning (DL) models applied to ...
I expect Pagaya to beat analysts’ revenue and EPS estimates when it reports Q4 earnings on February 9th. PGY’s estimated network volume growth and operating leverage could help offset a potential ...
Paper: Graph Representation of 3D CAD Models for Machining Feature Recognition With Deep Learning The MFCAD (Machining Feature CAD) dataset is a comprehensive collection of 3D CAD models with labeled ...
This repository provides an end-to-end pipeline for medical image segmentation using deep learning. Implemented in Python with TensorFlow, OpenCV, and other popular libraries, this project includes ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results