Zobrazeno 1 - 10
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pro vyhledávání: '"Ng, Andrew"'
Publikováno v:
Journal of the European Ceramic Society 44 (2024) 116696
Alumina microplatelets coated with a small amount of Fe3O4 can be oriented via a rotating magnetic field to create texture. After ultrafast high-temperature sintering (UHS), Fe atoms are found at the grain boundaries and within the grains, influencin
Externí odkaz:
http://arxiv.org/abs/2406.19585
Autor:
Jiang, Yixing, Irvin, Jeremy, Wang, Ji Hun, Chaudhry, Muhammad Ahmed, Chen, Jonathan H., Ng, Andrew Y.
Large language models are effective at few-shot in-context learning (ICL). Recent advancements in multimodal foundation models have enabled unprecedentedly long context windows, presenting an opportunity to explore their capability to perform ICL wit
Externí odkaz:
http://arxiv.org/abs/2405.09798
Autor:
Deshpande, Tanvi, Prakash, Eva, Ross, Elsie Gyang, Langlotz, Curtis, Ng, Andrew, Valanarasu, Jeya Maria Jose
The high cost of creating pixel-by-pixel gold-standard labels, limited expert availability, and presence of diverse tasks make it challenging to generate segmentation labels to train deep learning models for medical imaging tasks. In this work, we pr
Externí odkaz:
http://arxiv.org/abs/2404.17033
Autor:
Liu, Chih-Ying, Valanarasu, Jeya Maria Jose, Gonzalez, Camila, Langlotz, Curtis, Ng, Andrew, Gatidis, Sergios
Most deep learning models in medical imaging are trained on adult data with unclear performance on pediatric images. In this work, we aim to address this challenge in the context of automated anatomy segmentation in whole-body Computed Tomography (CT
Externí odkaz:
http://arxiv.org/abs/2404.13185
Autor:
Chaudhry, Muhammad Ahmed, Kim, Lyna, Irvin, Jeremy, Ido, Yuzu, Chu, Sonia, Isobe, Jared Thomas, Ng, Andrew Y., Watson-Parris, Duncan
Clouds play a significant role in global temperature regulation through their effect on planetary albedo. Anthropogenic emissions of aerosols can alter the albedo of clouds, but the extent of this effect, and its consequent impact on temperature chan
Externí odkaz:
http://arxiv.org/abs/2401.14486
Autor:
Srikanth, Maya, Irvin, Jeremy, Hill, Brian Wesley, Godoy, Felipe, Sabane, Ishan, Ng, Andrew Y.
Major advancements in computer vision can primarily be attributed to the use of labeled datasets. However, acquiring labels for datasets often results in errors which can harm model performance. Recent works have proposed methods to automatically ide
Externí odkaz:
http://arxiv.org/abs/2312.02200
Autor:
Irvin, Jeremy, Tao, Lucas, Zhou, Joanne, Ma, Yuntao, Nashold, Langston, Liu, Benjamin, Ng, Andrew Y.
Large, self-supervised vision models have led to substantial advancements for automatically interpreting natural images. Recent works have begun tailoring these methods to remote sensing data which has rich structure with multi-sensor, multi-spectral
Externí odkaz:
http://arxiv.org/abs/2312.02199
Autor:
Shankar, Vivek, Yang, Xiaoli, Krishna, Vrishab, Tan, Brent, Silva, Oscar, Rojansky, Rebecca, Ng, Andrew, Valvert, Fabiola, Briercheck, Edward, Weinstock, David, Natkunam, Yasodha, Fernandez-Pol, Sebastian, Rajpurkar, Pranav
The accurate classification of lymphoma subtypes using hematoxylin and eosin (H&E)-stained tissue is complicated by the wide range of morphological features these cancers can exhibit. We present LymphoML - an interpretable machine learning method tha
Externí odkaz:
http://arxiv.org/abs/2311.09574
Autor:
Van Uden, Cara, Irvin, Jeremy, Huang, Mars, Dean, Nathan, Carr, Jason, Ng, Andrew, Langlotz, Curtis
Self-supervised learning (SSL) enables label efficient training for machine learning models. This is essential for domains such as medical imaging, where labels are costly and time-consuming to curate. However, the most effective supervised or SSL st
Externí odkaz:
http://arxiv.org/abs/2305.08017