To speed up the optimization process, we transform the corresponding problem into a lower-dimensional latent space learned by a variational autoencoder. This is trained on a total of 6839 different 2D ...

A variational autoencoder is incorporated to enhance the system's robustness under various occlusion scenarios. Performance tests in real-world environments identified potential areas for improvement, ...

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework（Supports RGBT detection for all YOLO series from YOLOv3 to YOLOv12, as well as RTDETR. 【Ultralytics YOLOv ...

Notably, path reparameterization in the case of the V156A 3.40 mutant qualitatively improved the results, suggesting the importance of a system-dependent selection, as recently shown in unbinding ...

VITS (from Kakao Enterprise) released with the paper Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech by Jaehyeon Kim, Jungil Kong, Juhee Son.