From the 1 of 51 linked papers with an AI index.
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OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery
Hao Sheng, Jeremy Irvin, Sasankh Munukutla +10
At least a quarter of the warming that the Earth is experiencing today is due to anthropogenic methane emissions. There are multiple satellites in orbit and planned for launch in t…
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays
Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek +3
The use of smartphones to take photographs of chest x-rays represents an appealing solution for scaled deployment of deep learning models for chest x-ray interpretation. However, t…
GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video
Viswesh Krishna, Anirudh Joshi, Philip L. Bulterys +3
The application of deep learning to pathology assumes the existence of digital whole slide images of pathology slides. However, slide digitization is bottlenecked by the high cost…
ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery
Jeremy Irvin, Hao Sheng, Neel Ramachandran +7
Characterizing the processes leading to deforestation is critical to the development and implementation of targeted forest conservation and management policies. In this work, we de…
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models
Eric Zelikman, Sharon Zhou, Jeremy Irvin +7
Advancing probabilistic solar forecasting methods is essential to supporting the integration of solar energy into the electricity grid. In this work, we develop a variety of state-…
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng +1
Contrastive learning is a form of self-supervision that can leverage unlabeled data to produce pretrained models. While contrastive learning has demonstrated promising results on n…