We propose a statistical learning-based traffic speed estimation method that uses sparse vehicle trajectory information. Using a convolutional encoder-decoder based architecture, we show that a well ...

The aim of this research is to quickly detect cross-site scripting (XSS) attacks on the internet based on relationship diagram convolutional networks. Based on the principle and attack process of ...

What Is Image-to-Video AI and Why It Matters Image-to-video AI is a breakthrough in creative technology. It transforms static ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

How the brain largely maintains its function when neurons are lost—this is what researchers at the University Medical Center ...

Convolutional Neural Networks (ConvNets or CNNs) are a class of neural networks algorithms that are mostly used in visual recognition tasks such as image classification, object detection, and image ...

Moreover, it is possible to develop small and almost the same efficient neural network architectures, that our proposed architecture has the least parameters (around 2.4 millions) and spends the least ...

CoreNet is a deep neural network toolkit that allows researchers and engineers to train standard and novel small and large-scale models for variety of tasks, including foundation models (e.g., CLIP ...