Digestive system cancers, including hepatobiliary and gastrointestinal malignancies, remain a major global oncological burden ...
Abstract: Mainstream lane detection methods often lack flexibility, accuracy, and efficiency in challenging scenarios, especially with occlusion and extreme lighting. To address this, we reframe lane ...
Abstract: Deep-learned variational auto-encoders (VAE) have shown remarkable capabilities for lossy image compression. These neural networks typically employ non-linear convolutional layers for ...
We introduce VA-DepthNet, a simple, effective, and accurate deep neural network approach for the single-image depth prediction (SIDP) problem. The proposed approach advocates using classical ...
基于 条件变分自编码器 Conditional Variational Autoencoder, CVAE 的轻量级图像生成项目。 本项目可以使用一组图片进行训练 ...
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