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IWANN Special Collection 2019: Deep Learning Models in Healthcare and Biomedicine

IWANN Special Collection 2019: Deep Learning Models in Healthcare and Biomedicine
plos.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from plos.org Daily Mail and Mail on Sunday newspapers.

Byruxandra Stoean , Gonzalo Joya , Leonardo Franco , Miguel Atencia , International Work , University Of Malaga , Conference On Artificial Neural Networks , Electronics Technology , University Of Craiova , Associate Professor , Computer Science , Applied Mathematics , Deep Learning Models , International Work Conference , Artificial Neural Networks , Special Collection ,

PLOS Collections - Blogging about research and commentary published in PLOS Collections

Blogging about research and commentary published in PLOS Collections ....

T Ai Pei , Laura Cheever , Simon Allen , Ruxandra Stoean , Janr Baiker , Justin Wu , Nadia Castro , Veruska Muccione , Christian Huggel , Leonardo Franco , Catherine Chang , Iris Huang , Plos Complex Systemscomplex Networks , Medicine Health Sciencesiwann Special Collection , Services Administration , Human Services , Gem Team , Health Resources , Research Analysis Science Policyadvancing , Bureau Special Collection , University Of Craiova , Medicine Health Sciencesintroducing , Us Department Of Health , University Of Malaga , Systemscomplex Networks , Applications Conference ,

Research Validates Deep Learning Models for Drowning Diagnosis

Research Validates Deep Learning Models for Drowning Diagnosis
miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.

Japan General , Noriyasu Homma , Kei Ichiji , Jiaoyang Wang , Ivo Bukovsky , Yuwen Zeng , Akihito Usui , Xiaoyong Zhang , Masato Funayama , Shuoyan Chou , Tohoku University , Department Of Radiological Imaging , Tohoku University Graduate School Of Medicine , Tohoku University Graduate School , Imaging Informatics , Radiological Imaging , Human Observation , Deep Learning Models , Assessing Validity , Postmortem Computed Tomography Diagnosis ,

Team studies medical validity of deep learning models in diagnosing drowning

Team studies medical validity of deep learning models in diagnosing drowning
medicalxpress.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from medicalxpress.com Daily Mail and Mail on Sunday newspapers.

Japan General , Yuwen Zeng , Tohoku University , Department Of Radiological Imaging , Tohoku University Graduate School Of Medicine , Tohoku University Graduate School , Imaging Informatics , Radiological Imaging , Human Observation , Deep Learning Models , Assessing Validity , Postmortem Computed Tomography Diagnosis ,

"The Role of Deep Learning Models in the Detection of Anti-Social Behav" by Marcella Papini, Umair Iqbal et al.

Increasing women’s active participation in economic, educational, and social spheres requires ensuring safe public transport environments. This study investigates the potential of machine learning-based models in addressing behaviours impacting the safety perception of women commuters. Specifically, we conduct a comprehensive review of the existing literature concerning the utilisation of deep learning models for identifying anti-social behaviours in public spaces. Employing a scoping review methodology, our study synthesises the current landscape, highlighting both the advantages and challenges associated with the automated detection of such behaviours. Additionally, we assess available video and audio datasets suitable for training detection algorithms in this context. The findings not only shed light on the feasibility of leveraging deep learning for recognising anti-social behaviours but also provide critical insights for researchers, developers, and transport operators. Our work ....

Anti Social Behaviour Detection , Deep Learning Models , Public Transport , Safe Transportation , Womens Safety ,