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Convolutional Neural Networks in Multi-Class Classification of Medical Data
We report applications of Convolutional Neural Networks (CNN) to multi-c...
12/28/2020 ∙ by YuanZheng Hu, et al. ∙
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Image Pre-processing on NumtaDB for Bengali Handwritten Digit Recognition
NumtaDB is by far the largest data-set collection for handwritten digits...
08/18/2020 ∙ by Ovi Paul, et al. ∙
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A Novel Chaos Theory Inspired Neuronal Architecture
The practical success of widely used machine learning (ML) and deep lear...
05/19/2019 ∙ by Harikrishnan N B, et al. ∙
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The TrojAI Software Framework: An OpenSource tool for Embedding Trojans into Deep Learning Models
In this paper, we introduce the TrojAI software framework, an open sourc...
03/13/2020 ∙ by Kiran Karra, et al. ∙
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Symbolic Execution for Deep Neural Networks
Deep Neural Networks (DNN) are increasingly used in a variety of applica...
07/27/2018 ∙ by Divya Gopinath, et al. ∙
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Bilinear Models for Machine Learning
In this work we define and analyze the bilinear models which replace the...
12/06/2019 ∙ by Tayssir Doghri, et al. ∙
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S^2-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning
This paper proposes a novel Stochastic Split Linearized Bregman Iteratio...
04/24/2019 ∙ by Yanwei Fu, et al. ∙
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Tamil Vowel Recognition With Augmented MNIST-like Data Set
06/09/2020 ∙ by Muthiah Annamalai, et al. ∙
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We report generation of a MNIST [4] compatible data set [1] for Tamil vowels to enable building a classification DNN or other such ML/AI deep learning [2] models for Tamil OCR/Handwriting applications. We report the capability of the 60,000 grayscale, 28x28 pixel dataset to build a 92 82 also report a top-1 classification accuracy of 70 accuracy of 92
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