This study proposes the IoT-Enhanced Pose Optimization Network (IE-PONet) for high-
precision 3D pose estimation and motion optimization of track and field athletes. IE-PONet …

This study introduces a method for efficiently detecting objects within 3D point clouds using
convolutional neural networks (CNNs). Our approach adopts a unique feature-centric voting …

With the intensification of global aging, health management of the elderly has become a
focus of social attention. This study designs and implements a smart elderly care service …

In the healthcare sector, the application of deep learning technologies has revolutionized
data analysis and disease forecasting. This is particularly evident in the field of diabetes …

This paper explores the application of the Temporal Fusion Transformer (TFT) model in
demand forecasting within supply chain management. The TFT model leverages multi-head …

Complex scene comprehension is an increasingly vital field in computer vision, driven by
applications ranging from autonomous vehicles to medical imaging. AI-driven object …

Fundus image segmentation is a critical process in medical imaging, enabling precise
delineation of retinal structures for diagnosing and monitoring ophthalmic conditions …

This paper introduces TrafficNet-ST, a Spatial-Temporal Graph Convolutional Network (ST-
GCN) model designed to predict real-time traffic flow in urban transportation systems …

This paper presents EcoDiff, a novel application of Diffusion Models for automated waste
classification, aiming to enhance recycling efficiency and support sustainable resource …

This paper explores the application of the N-BEATS (Neural Basis Expansion Analysis for
Time Series) model in demand forecasting within the supply chain management (SCM) …