50 citations · 77 across the 10 of their papers we have counts for
10 papers
Adversarial Attacks with Time-Scale Representations
Alberto Santamaria-Pang, Jianwei Qiu, Aritra Chowdhury +4
We propose a novel framework for real-time black-box universal attacks which disrupts activations of early convolutional layers in deep learning models. Our hypothesis is that pert…
Symbolic Semantic Segmentation and Interpretation of COVID-19 Lung Infections in Chest CT volumes based on Emergent Languages
Aritra Chowdhury, Alberto Santamaria-Pang, James R. Kubricht +2
The coronavirus disease (COVID-19) has resulted in a pandemic crippling the a breadth of services critical to daily life. Segmentation of lung infections in computerized tomography…
Emergent symbolic language based deep medical image classification
Aritra Chowdhury, Alberto Santamaria-Pang, James R. Kubricht +1
Modern deep learning systems for medical image classification have demonstrated exceptional capabilities for distinguishing between image based medical categories. However, they ar…
Towards Emergent Language Symbolic Semantic Segmentation and Model Interpretability
Alberto Santamaria-Pang, James Kubricht, Aritra Chowdhury +2
Recent advances in methods focused on the grounding problem have resulted in techniques that can be used to construct a symbolic language associated with a specific domain. Inspire…
Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships
Wufei Ma, Elizabeth Kautz, Arun Baskaran +4
We investigate methods of microstructure representation for the purpose of predicting processing condition from microstructure image data. A binary alloy (uranium-molybdenum) that…
Automated Phenotyping via Cell Auto Training (CAT) on the Cell DIVE Platform
Alberto Santamaria-Pang, Anup Sood, Dan Meyer +2
We present a method for automatic cell classification in tissue samples using an automated training set from multiplexed immunofluorescence images. The method utilizes multiple mar…
ESCELL: Emergent Symbolic Cellular Language
Aritra Chowdhury, James R. Kubricht, Anup Sood +2
We present ESCELL, a method for developing an emergent symbolic language of communication between multiple agents reasoning about cells. We show how agents are able to cooperate an…
FastEstimator: A Deep Learning Library for Fast Prototyping and Productization
Xiaomeng Dong, Junpyo Hong, Hsi-Ming Chang +10
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 pr…
Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines
Aritra Chowdhury, Malik Magdin-Ismail, Bulent Yener
Data science relies on pipelines that are organized in the form of interdependent computational steps. Each step consists of various candidate algorithms that maybe used for perfor…
Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines
Aritra Chowdhury, Malik Magdon-Ismail, Bulent Yener
Data science relies on pipelines that are organized in the form of interdependent computational steps. Each step consists of various candidate algorithms that maybe used for perfor…