Zobrazeno 1 - 10
of 944
pro vyhledávání: '"Multi modal training"'
An electrocardiogram (ECG) captures the heart's electrical signal to assess various heart conditions. In practice, ECG data is stored as either digitized signals or printed images. Despite the emergence of numerous deep learning models for digitized
Externí odkaz:
http://arxiv.org/abs/2408.02888
Recently, there has been a surge in the popularity of pre trained large language models (LLMs) (such as GPT-4), sweeping across the entire Natural Language Processing (NLP) and Computer Vision (CV) communities. These LLMs have demonstrated advanced m
Externí odkaz:
http://arxiv.org/abs/2401.03851
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Multi-modal large language models (MLLMs) are trained based on large language models (LLM), with an enhanced capability to comprehend multi-modal inputs and generate textual responses. While they excel in multi-modal tasks, the pure NLP abilities of
Externí odkaz:
http://arxiv.org/abs/2309.07120
To let the state-of-the-art end-to-end ASR model enjoy data efficiency, as well as much more unpaired text data by multi-modal training, one needs to address two problems: 1) the synchronicity of feature sampling rates between speech and language (ak
Externí odkaz:
http://arxiv.org/abs/2211.00325
Oversight AI is an emerging concept in radiology where the AI forms a symbiosis with radiologists by continuously supporting radiologists in their decision-making. Recent advances in vision-language models sheds a light on the long-standing problems
Externí odkaz:
http://arxiv.org/abs/2208.05140
Publikováno v:
In Medical Image Analysis January 2024 91
Computer-assisted multimodal training is an effective way of learning complex motor skills in various applications. In particular disciplines (eg. healthcare) incompetency in performing dexterous hands-on examinations (clinical palpation) may result
Externí odkaz:
http://arxiv.org/abs/2001.05745
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Rosenfeldt, Anson B., Penko, Amanda L., Streicher, Matthew C., Zimmerman, Nicole M., Koop, Mandy Miller, Alberts, Jay L.
Publikováno v:
In Parkinsonism and Related Disorders July 2019 64:280-285