Výsledky vyhledávání - "Johnson, Jeremiah W."

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A Contrastive Learning Approach to Auroral Identification and Classification

Autor: Johnson, Jeremiah W., Hari, Swathi, Hampton, Donald, Connor, Hyunju K., Keesee, Amy

Publikováno v: Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, Dec. 2021

Unsupervised learning algorithms are beginning to achieve accuracies comparable to their supervised counterparts on benchmark computer vision tasks, but their utility for practical applications has not yet been demonstrated. In this work, we present

Externí odkaz: http://arxiv.org/abs/2109.13899

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Detecting Invasive Ductal Carcinoma with Semi-Supervised Conditional GANs

Autor: Johnson, Jeremiah W.

Publikováno v: Proceedings of the Future Technologies Conference (FTC) 2020, vol. 3, pp.113-120

Invasive ductal carcinoma (IDC) comprises nearly 80% of all breast cancers. The detection of IDC is a necessary preprocessing step in determining the aggressiveness of the cancer, determining treatment protocols, and predicting patient outcomes, and

Externí odkaz: http://arxiv.org/abs/1911.06216

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On the Diophantine Equation 1/a + 1/b = (q+1) / pq

Autor: Johnson, Jeremiah W.

Let $p$ and $q$ be distinct primes such that $q+1 | p-1$. In this paper we find all integer solutions $a$, $b$ to the equation $1/a + 1/b = (q+1)/pq$ using only elementary methods.

Externí odkaz: http://arxiv.org/abs/1905.03056

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Structured Prediction using cGANs with Fusion Discriminator

Autor: Mahmood, Faisal, Xu, Wenhao, Durr, Nicholas J., Johnson, Jeremiah W., Yuille, Alan

Publikováno v: Workshop on Deep Generative Models for Structured Prediction at ICLR 2019

We propose the fusion discriminator, a single unified framework for incorporating conditional information into a generative adversarial network (GAN) for a variety of distinct structured prediction tasks, including image synthesis, semantic segmentat

Externí odkaz: http://arxiv.org/abs/1904.13358

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Adapting Mask-RCNN for Automatic Nucleus Segmentation

Autor: Johnson, Jeremiah W.

Publikováno v: Proceedings of the 2019 Computer Vision Conference, Vol. 2

Automatic segmentation of microscopy images is an important task in medical image processing and analysis. Nucleus detection is an important example of this task. Mask-RCNN is a recently proposed state-of-the-art algorithm for object detection, objec

Externí odkaz: http://arxiv.org/abs/1805.00500

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