Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Rohanian, Morteza"'
Autor:
Kim, Sanghwan, Nooralahzadeh, Farhad, Rohanian, Morteza, Fujimoto, Koji, Nishio, Mizuho, Sakamoto, Ryo, Rinaldi, Fabio, Krauthammer, Michael
Recent transformer-based models have made significant strides in generating radiology reports from chest X-ray images. However, a prominent challenge remains: these models often lack prior knowledge, resulting in the generation of synthetic reports t
Externí odkaz:
http://arxiv.org/abs/2305.04561
Autor:
Rohanian, Omid, Kouchaki, Samaneh, Soltan, Andrew, Yang, Jenny, Rohanian, Morteza, Yang, Yang, Clifton, David
Early detection of COVID-19 is an ongoing area of research that can help with triage, monitoring and general health assessment of potential patients and may reduce operational strain on hospitals that cope with the coronavirus pandemic. Different mac
Externí odkaz:
http://arxiv.org/abs/2201.03004
We present two multimodal fusion-based deep learning models that consume ASR transcribed speech and acoustic data simultaneously to classify whether a speaker in a structured diagnostic task has Alzheimer's Disease and to what degree, evaluating the
Externí odkaz:
http://arxiv.org/abs/2106.15684
Publikováno v:
Proc. Interspeech 2020, 2187-2191
This paper is a submission to the Alzheimer's Dementia Recognition through Spontaneous Speech (ADReSS) challenge, which aims to develop methods that can assist in the automated prediction of severity of Alzheimer's Disease from speech data. We focus
Externí odkaz:
http://arxiv.org/abs/2106.09668
Autor:
Rohanian, Morteza, Hough, Julian
Publikováno v:
The 28th International Conference on Computational Linguistics (COLING 2020)
We present a multi-task learning framework to enable the training of one universal incremental dialogue processing model with four tasks of disfluency detection, language modelling, part-of-speech tagging, and utterance segmentation in a simple deep
Externí odkaz:
http://arxiv.org/abs/2011.06754
With the social media engagement on the rise, the resulting data can be used as a rich resource for analyzing and understanding different phenomena around us. A sentiment analysis system employs these data to find the attitude of social media users t
Externí odkaz:
http://arxiv.org/abs/2002.06233
Autor:
Rohanian, Omid, Kouchaki, Samaneh, Soltan, Andrew, Yang, Jenny, Rohanian, Morteza, Yang, Yang, Clifton, David
Publikováno v:
IEEE Journal of Biomedical and Health Informatics; 2023, Vol. 27 Issue: 3 p1249-1258, 10p
Publikováno v:
Annual International Conference on Information Technology & Applications; 2015, p59-62, 4p
Publikováno v:
IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2022 Dec 20; Vol. PP. Date of Electronic Publication: 2022 Dec 20.