Deep reinforcement learning (DRL) has emerged as a promising solution for autonomous operations of autonomous aerial vehicles (AAVs) in unknown environments. However, learning to navigate and avoid ...

Currently, the traffic speed prediction model based on deep learning has become a research hotspot in the field of transportation. With the rapid development of deep learning and the improvement of ...

Keywords: computational model, microbe-disease associations, bilinear attention networks, sparse autoencoder, prediction Citation: Liu X, Liang M, Yu G, Tang S, Wu O, Zeng B and Wang L (2025) BANSMDA: ...

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech Jaehyeon Kim, Jungil Kong, and Juhee Son In our recent paper, we propose VITS: Conditional Variational ...

Furthermore, a hybrid approach combining U-Net with Kalman filtering was explored to enhance performance. The results demonstrate the superiority of deep learning methods in denoising gyroscope data, ...

Image Denoising with Autoencoders in R (University Project) Built a convolutional autoencoder in R using Keras/TensorFlow to perform image denoising on MNIST and CIFAR-10 datasets with varying levels ...