Abstract: Speech enhancement (SE) models based on deep neural networks (DNNs) have shown excellent denoising performance. However, mainstream SE models often have high structural complexity and large ...

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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 ...

Abstract: U-shaped encoder-decoder convolutional neural networks have shown significant success in medical image segmentation. However, these networks often face challenges, including detail loss in ...

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 ...

Beyond tumor-shed markers: AI driven tumor-educated polymorphonuclear granulocytes monitoring for multi-cancer early detection. Clinical outcomes of a prospective multicenter study evaluating a ...