Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of ...

Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...

We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...

If you are a tech fanatic, you may have heard of the Mu Language Model from Microsoft. It is an SLM, or a Small Language Model, that runs on your device locally. Unlike cloud-dependent AIs, MU ...

Abstract: Surgical tool segmentation is used for detection, tracking and pose estimation of the tools in the vicinity of surgical scenes. It is considered as an essential task in surgical phase ...

DeepEP is a communication library designed for Mixture-of-Experts and expert parallelism, featuring high-throughput, low-latency GPU kernels. It supports low-precision operations and offers optimized ...

Abstract: This article presents a new deep-learning architecture based on an encoder-decoder framework that retains contrast while performing background subtraction (BS) on thermal videos. The ...

I congratulate you for this paper being cited multiple times recently, I am just confused about the basic architecture written in the code, as it was mentioned in the basic form the variables of ...