DraftAid is a Toronto-based company. Its tool automates the process of converting 3D CAD models into 2D drawings, empowering ...

Abstract: Electrolaryngeal (EL) speech utilizes excitation signals generated by an electrolarynx instead of human vocal vibrations. In daily communication, EL speech is less natural and more difficult ...

Abstract: Address event representation (AER) object recognition task has attracted extensive attention in neuromorphic vision processing. The spike-based and event-driven computation inherent in the ...

To build a self-supervised magnetic resonance imaging (MRI) foundation model from routine clinical scans and to test whether it can support key glioma-related applications, including post-therapy ...

Chinese artificial intelligence developer Moonshot AI today debuted Kimi K2.5, an open-source model that it says can outperform GPT-5.2 across several benchmarks. The launch comes a few days after ...

We cross-validated four pretrained Bidirectional Encoder Representations from Transformers (BERT)–based models—BERT, BioBERT, ClinicalBERT, and MedBERT—by fine-tuning them on 90% of 3,261 sentences ...

Background: Artificial intelligence (AI) can diagnose a wide array of cardiac conditions from electrocardiograms (ECGs). Wearable and portable ECG devices may enable expanded AI-based screening for ...

I found out people are making Chroma models with the VAE & Text encoder in the model instead of separate models. Which is super useful for lower Vram users. I read on the page below that Forge doesn't ...

I tried to use vjepa2_vit_large model to do inference. Although the scale of parameters is about 300M, the memory consumption is about 40GB. I wonder why it is so large and can you optimize this part?

Gene expression is the process through which genetic information in DNA is converted into functional products, primarily proteins. This involves two main steps: transcription, where DNA is copied into ...