Search Results for author: Aritra Chowdhury

Found 10 papers, 2 papers with code

Adversarial Attacks with Time-Scale Representations

no code implementations26 Jul 2021 Alberto Santamaria-Pang, Jianwei Qiu, Aritra Chowdhury, James Kubricht, Peter Tu, Iyer Naresh, Nurali Virani

Third, we generate new adversarial images by projecting back the original coefficients from the low scale and the perturbed coefficients from the high scale sub-space.

Emergent symbolic language based deep medical image classification

1 code implementation22 Aug 2020 Aritra Chowdhury, Alberto Santamaria-Pang, James R. Kubricht, Peter Tu

In this work, we demonstrate for the first time, the emer-gence of deep symbolic representations of emergent language in the frame-work of image classification.

Classification Decision Making +3

Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships

no code implementations27 Jul 2020 Wufei Ma, Elizabeth Kautz, Arun Baskaran, Aritra Chowdhury, Vineet Joshi, Bülent Yener, Daniel Lewis

A binary alloy (uranium-molybdenum) that is currently under development as a nuclear fuel was studied for the purpose of developing an improved machine learning approach to image recognition, characterization, and building predictive capabilities linking microstructure to processing conditions.

Towards Emergent Language Symbolic Semantic Segmentation and Model Interpretability

no code implementations18 Jul 2020 Alberto Santamaria-Pang, James Kubricht, Aritra Chowdhury, Chitresh Bhushan, Peter Tu

A UNet-like architecture is used to generate input to the Sender network which produces a symbolic sentence, and a Receiver network co-generates the segmentation mask based on the sentence.

Semantic Segmentation

ESCELL: Emergent Symbolic Cellular Language

no code implementations18 Jul 2020 Aritra Chowdhury, James R. Kubricht, Anup Sood, Peter Tu, Alberto Santamaria-Pang

In one form of the game, a sender and a receiver observe a set of cells from 5 different cell phenotypes.

Automated Phenotyping via Cell Auto Training (CAT) on the Cell DIVE Platform

no code implementations18 Jul 2020 Alberto Santamaria-Pang, Anup Sood, Dan Meyer, Aritra Chowdhury, Fiona Ginty

We present a method for automatic cell classification in tissue samples using an automated training set from multiplexed immunofluorescence images.

General Classification

FastEstimator: A Deep Learning Library for Fast Prototyping and Productization

no code implementations7 Oct 2019 Xiaomeng Dong, Jun-Pyo Hong, Hsi-Ming Chang, Michael Potter, Aritra Chowdhury, Purujit Bahl, Vivek Soni, Yun-chan Tsai, Rajesh Tamada, Gaurav Kumar, Caroline Favart, V. Ratna Saripalli, Gopal Avinash

As the complexity of state-of-the-art deep learning models increases by the month, implementation, interpretation, and traceability become ever-more-burdensome challenges for AI practitioners around the world.

Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines

no code implementations25 Feb 2019 Aritra Chowdhury, Malik Magdin-Ismail, Bulent Yener

We show that algorithm selection and hyper-parameter optimization methods can be used to quantify the error contribution and that random search is able to quantify the contribution more accurately than Bayesian optimization.

General Classification Image Classification

Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines

1 code implementation21 Feb 2019 Aritra Chowdhury, Malik Magdon-Ismail, Bulent Yener

The agnostic and naive methodologies quantify the error contribution and propagation respectively from the computational steps, algorithms and hyperparameters in the image classification pipeline.

General Classification Hyperparameter Optimization +1

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