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of 2 371
pro vyhledávání: '"BROWN, DONALD A."'
Domain adaptive semantic segmentation is the task of generating precise and dense predictions for an unlabeled target domain using a model trained on a labeled source domain. While significant efforts have been devoted to improving unsupervised domai
Externí odkaz:
http://arxiv.org/abs/2410.16485
Autor:
Moradinasab, Nazanin, Shankman, Laura S., Deaton, Rebecca A., Owens, Gary K., Brown, Donald E.
Domain adaptive semantic segmentation aims to generate accurate and dense predictions for an unlabeled target domain by leveraging a supervised model trained on a labeled source domain. The prevalent self-training approach involves retraining the den
Externí odkaz:
http://arxiv.org/abs/2406.19225
Autor:
Blanks, Zachary, Brown, Donald E.
Quantifying the complexity and irregularity of time series data is a primary pursuit across various data-scientific disciplines. Sample entropy (SampEn) is a widely adopted metric for this purpose, but its reliability is sensitive to the choice of it
Externí odkaz:
http://arxiv.org/abs/2405.06112
Eosinophilic Esophagitis (EoE) represents a challenging condition for medical providers today. The cause is currently unknown, the impact on a patient's daily life is significant, and it is increasing in prevalence. Traditional approaches for medical
Externí odkaz:
http://arxiv.org/abs/2403.11323
Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT
Autor:
Sengupta, Saurav, Brown, Donald E.
Deep learning for histopathology has been successfully used for disease classification, image segmentation and more. However, combining image and text modalities using current state-of-the-art (SOTA) methods has been a challenge due to the high resol
Externí odkaz:
http://arxiv.org/abs/2312.01435
Autor:
Sengupta, Saurav, Brown, Donald E.
Deep learning for histopathology has been successfully used for disease classification, image segmentation and more. However, combining image and text modalities using current state-of-the-art methods has been a challenge due to the high resolution o
Externí odkaz:
http://arxiv.org/abs/2311.06176
Eosinophilic Esophagitis (EoE) is an allergic condition increasing in prevalence. To diagnose EoE, pathologists must find 15 or more eosinophils within a single high-power field (400X magnification). Determining whether or not a patient has EoE can b
Externí odkaz:
http://arxiv.org/abs/2309.16536
Autor:
Moradinasab, Nazanin, Deaton, Rebecca A., Shankman, Laura S., Owens, Gary K., Brown, Donald E.
Recently, deep learning-based methods achieved promising performance in nuclei detection and classification applications. However, training deep learning-based methods requires a large amount of pixel-wise annotated data, which is time-consuming and
Externí odkaz:
http://arxiv.org/abs/2309.03744
Autor:
Guleria, Shan, Schwartz, Benjamin, Sharma, Yash, Fernandes, Philip, Jablonski, James, Adewole, Sodiq, Srivastava, Sanjana, Rhoads, Fisher, Porter, Michael, Yeghyayan, Michelle, Hyatt, Dylan, Copland, Andrew, Ehsan, Lubaina, Brown, Donald, Syed, Sana
Introduction: Technical burdens and time-intensive review processes limit the practical utility of video capsule endoscopy (VCE). Artificial intelligence (AI) is poised to address these limitations, but the intersection of AI and VCE reveals challeng
Externí odkaz:
http://arxiv.org/abs/2308.13035