ABSTRACT: Cognitive impairment is a frequent and debilitating outcome of stroke, profoundly affecting patient independence, recovery trajectories, and long-term quality of life. Despite its prevalence ...

Abstract: Deep neural network and Machine learning are a latest emerging concept in the field of data science. Due to multi-layer hierarchical feature extraction in conjunction with control variables ...

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...

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Abstract: The classification of agricultural crops such as cassava, corn, rice, and sugarcane is crucial for efficient data collection and decision-making. However, the limited availability of labeled ...

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本项目基于 PyTorch，围绕 CIFAR-10 数据集，集成了模型训练、评估、推理、特征可视化和 Web 交互界面等功能，旨在实现一个完整的深度学习图像分类与可解释性分析平台。支持 ResNet-18 预训练模型微调，具备丰富的可视化与交互体验，适合教学、科研和工程实践。