70 citations · 192 across the 16 of their papers we have counts for
18 papers
Collisionless Pattern Discovery in Robot Swarms Using Deep Reinforcement Learning
Nelson Sharma, Aswini Ghosh, Rajiv Misra +2
We present a deep reinforcement learning-based framework for automatically discovering patterns available in any given initial configuration of fat robot swarms. In particular, we…
A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium
Qun Liu, Supratik Mukhopadhyay, Maria Ximena Bastidas Rodriguez +4
Myocardial infarction (MI) is a scientific term that refers to heart attack. In this study, we infer highly relevant second harmonic generation (SHG) cues from collagen fibers exhi…
DeepSat V2: Feature Augmented Convolutional Neural Nets for Satellite Image Classification
Qun Liu, Saikat Basu, Sangram Ganguly +4
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning. Due to the high variability inherent i…
PCGAN-CHAR: Progressively Trained Classifier Generative Adversarial Networks for Classification of Noisy Handwritten Bangla Characters
Qun Liu, Edward Collier, Supratik Mukhopadhyay
Due to the sparsity of features, noise has proven to be a great inhibitor in the classification of handwritten characters. To combat this, most techniques perform denoising of the…
Improving Prediction Accuracy in Building Performance Models Using Generative Adversarial Networks (GANs)
Chanachok Chokwitthaya, Edward Collier, Yimin Zhu +1
Building performance discrepancies between building design and operation are one of the causes that lead many new designs fail to achieve their goals and objectives. One of main fa…
Why do you take that route?
Alimire Nabijiang, Supratik Mukhopadhyay, Yimin Zhu +3
The purpose of this paper is to determine whether a particular context factor among the variables that a researcher is interested in causally affects the route choice behavior of d…
Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation
Qun Liu, Supratik Mukhopadhyay, Yimin Zhu +3
Route Choice Models predict the route choices of travelers traversing an urban area. Most of the route choice models link route characteristics of alternative routes to those chose…
Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images
Edward Collier, Kate Duffy, Sangram Ganguly +8
Machine learning has proven to be useful in classification and segmentation of images. In this paper, we evaluate a training methodology for pixel-wise segmentation on high resolut…
Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters
Manohar Karki, Qun Liu, Robert DiBiano +2
Classification techniques for images of handwritten characters are susceptible to noise. Quadtrees can be an efficient representation for learning from sparse features. In this pap…
Unsupervised Learning using Pretrained CNN and Associative Memory Bank
Qun Liu, Supratik Mukhopadhyay
Deep Convolutional features extracted from a comprehensive labeled dataset, contain substantial representations which could be effectively used in a new domain. Despite the fact th…
CactusNets: Layer Applicability as a Metric for Transfer Learning
Edward Collier, Robert DiBiano, Supratik Mukhopadhyay
Deep neural networks trained over large datasets learn features that are both generic to the whole dataset, and specific to individual classes in the dataset. Learned features tend…
Core Sampling Framework for Pixel Classification
Manohar Karki, Robert DiBiano, Saikat Basu +1
The intermediate map responses of a Convolutional Neural Network (CNN) contain information about an image that can be used to extract contextual knowledge about it. In this paper,…
A Theoretical Analysis of Deep Neural Networks for Texture Classification
Saikat Basu, Manohar Karki, Robert DiBiano +4
We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative represe…
OptCon: An Adaptable SLA-Aware Consistency Tuning Framework for Quorum-based Stores
Subhajit Sidhanta, Wojciech Golab, Supratik Mukhopadhyay +1
Users of distributed datastores that employ quorum-based replication are burdened with the choice of a suitable client-centric consistency setting for each storage operation. The a…
OptEx: A Deadline-Aware Cost Optimization Model for Spark
Subhajit Sidhanta, Wojciech Golab, Supratik Mukhopadhyay
We present OptEx, a closed-form model of job execution on Apache Spark, a popular parallel processing engine. To the best of our knowledge, OptEx is the first work that analyticall…
Automatic Synthesis of Geometry Problems for an Intelligent Tutoring System
Chris Alvin, Sumit Gulwani, Rupak Majumdar +1
This paper presents an intelligent tutoring system, GeoTutor, for Euclidean Geometry that is automatically able to synthesize proof problems and their respective solutions given a…
DeepSat - A Learning framework for Satellite Imagery
Saikat Basu, Sangram Ganguly, Supratik Mukhopadhyay +3
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning. Due to the high variability inherent i…
Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets
Saikat Basu, Manohar Karki, Sangram Ganguly +3
Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem. In this paper, we present three labeled handwritten digit datasets, col…