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 ...
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 ...
Power Solutions International is deeply undervalued despite robust earnings growth and a strategic pivot toward high-margin data center power systems. PSIX trades at 14x 2025 earnings, a steep ...
Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...
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