Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Hannan, Darryl"'
Autor:
Hannan, Darryl, Nesbit, Steven C., Wen, Ximing, Smith, Glen, Zhang, Qiao, Goffi, Alberto, Chan, Vincent, Morris, Michael J., Hunninghake, John C., Villalobos, Nicholas E., Kim, Edward, Weber, Rosina O., MacLellan, Christopher J.
Detecting elevated intracranial pressure (ICP) is crucial in diagnosing and managing various neurological conditions. These fluctuations in pressure are transmitted to the optic nerve sheath (ONS), resulting in changes to its diameter, which can then
Externí odkaz:
http://arxiv.org/abs/2403.02236
Autor:
Hannan, Darryl, Arnab, Ragib, Parpart, Gavin, Kenyon, Garrett T., Kim, Edward, Watkins, Yijing
Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such as object d
Externí odkaz:
http://arxiv.org/abs/2402.06805
Autor:
Hannan, Darryl, Nesbit, Steven C., Wen, Ximing, Smith, Glen, Zhang, Qiao, Goffi, Alberto, Chan, Vincent, Morris, Michael J., Hunninghake, John C., Villalobos, Nicholas E., Kim, Edward, Weber, Rosina O., MacLellan, Christopher J.
Point-of-Care Ultrasound (POCUS) refers to clinician-performed and interpreted ultrasonography at the patient's bedside. Interpreting these images requires a high level of expertise, which may not be available during emergencies. In this paper, we su
Externí odkaz:
http://arxiv.org/abs/2212.03282
Recent advances in text-to-image synthesis have led to large pretrained transformers with excellent capabilities to generate visualizations from a given text. However, these models are ill-suited for specialized tasks like story visualization, which
Externí odkaz:
http://arxiv.org/abs/2209.06192
Story visualization is an under-explored task that falls at the intersection of many important research directions in both computer vision and natural language processing. In this task, given a series of natural language captions which compose a stor
Externí odkaz:
http://arxiv.org/abs/2105.10026
We present a new multimodal question answering challenge, ManyModalQA, in which an agent must answer a question by considering three distinct modalities: text, images, and tables. We collect our data by scraping Wikipedia and then utilize crowdsourci
Externí odkaz:
http://arxiv.org/abs/2001.08034
Deep feed-forward convolutional neural networks (CNNs) have become ubiquitous in virtually all machine learning and computer vision challenges; however, advancements in CNNs have arguably reached an engineering saturation point where incremental nove
Externí odkaz:
http://arxiv.org/abs/1711.07998