no code implementations • 25 Apr 2024 • Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob Foerster
In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education.
1 code implementation • 1 Aug 2022 • Frej Berglind, Haron Temam, Supratik Mukhopadhyay, Kamalika Das, Md Saiful Islam Sajol, Sricharan Kumar, Kumar Kallurupalli
Detecting out-of-distribution (OOD) data at inference time is crucial for many applications of machine learning.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
no code implementations • 17 Feb 2021 • Sridhar Tripathy, Jaydeep Datta, Nayana Majumdar, Supratik Mukhopadhyay
The images of the test cases with and without the defect have been simulated for a month-long exposure of cosmic muons on the basis of their scattering from the composite concrete structures.
High Energy Physics - Experiment Image and Video Processing Instrumentation and Detectors
no code implementations • 5 Nov 2020 • Prasant Kumar Rout, Jaydeep Datta, Promita Roy, Purba Bhattacharya, Supratik Mukhopadhyay, Nayana Majumdar, Sandip Sarkar
A fast, hydrodynamic numerical model has been developed on the COMSOL Multi-physics platform to simulate the evolution and dynamics of charged particles in gaseous ionization detectors based on the Gaseous Electron Multipliers (GEM).
Instrumentation and Detectors High Energy Physics - Experiment
no code implementations • 23 Jan 2020 • Qun Liu, Supratik Mukhopadhyay, Maria Ximena Bastidas Rodriguez, Xing Fu, Sushant Sahu, David Burk, Manas Gartia
Myocardial infarction (MI) is a scientific term that refers to heart attack.
no code implementations • 7 Jan 2020 • Supratik Mukhopadhyay, Qun Liu, Edward Collier, Yimin Zhu, Ravindra Gudishala, Chanachok Chokwitthaya, Robert DiBiano, Alimire Nabijiang, Sanaz Saeidi, Subhajit Sidhanta, Arnab Ganguly
The impacts of context factors driving human system interaction are challenging and are difficult to capture and replicate in existing design models.
1 code implementation • 15 Nov 2019 • Qun Liu, Saikat Basu, Sangram Ganguly, Supratik Mukhopadhyay, Robert DiBiano, Manohar Karki, Ramakrishna Nemani
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning.
Ranked #1 on Satellite Image Classification on SAT-4
no code implementations • 11 Aug 2019 • Qun Liu, Edward Collier, Supratik Mukhopadhyay
We show that by learning the features at each resolution independently a trained model is able to accurately classify characters even in the presence of noise.
Ranked #1 on Image Classification on Noisy MNIST (AWGN)
no code implementations • 13 Jun 2019 • Chanachok Chokwitthaya, Edward Collier, Yimin Zhu, Supratik Mukhopadhyay
To potentially reduce the discrepancies and improve the prediction accuracy of BPMs, this paper proposes a computational framework for learning mixture models by using Generative Adversarial Networks (GANs) that appropriately combining existing BPMs with knowledge on occupant behaviors to contextual factors in new designs.
no code implementations • 27 Mar 2019 • Qun Liu, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala, Sanaz Saeidi, Alimire Nabijiang
High fidelity route choice models are required to predict traffic levels with higher accuracy.
no code implementations • 12 Feb 2019 • Edward Collier, Kate Duffy, Sangram Ganguly, Geri Madanguit, Subodh Kalia, Gayaka Shreekant, Ramakrishna Nemani, Andrew Michaelis, Shuang Li, Auroop Ganguly, Supratik Mukhopadhyay
Machine learning has proven to be useful in classification and segmentation of images.
no code implementations • 21 Jun 2018 • Manohar Karki, Qun Liu, Robert DiBiano, Saikat Basu, Supratik Mukhopadhyay
Classification techniques for images of handwritten characters are susceptible to noise.
Ranked #1 on Document Image Classification on n-MNIST
no code implementations • 2 May 2018 • Qun Liu, Supratik Mukhopadhyay
In this paper, we present a new architecture and an approach for unsupervised object recognition that addresses the above mentioned problem with fine tuning associated with pretrained CNN-based supervised deep learning approaches while allowing automated feature extraction.
Ranked #1 on Fine-Grained Image Classification on Caltech-101 (Accuracy metric)
Few-Shot Image Classification Fine-Grained Image Classification +2
no code implementations • 20 Apr 2018 • 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.
no code implementations • 6 Dec 2016 • Manohar Karki, Robert DiBiano, Saikat Basu, Supratik Mukhopadhyay
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.
no code implementations • 9 May 2016 • Saikat Basu, Manohar Karki, Robert DiBiano, Supratik Mukhopadhyay, Sangram Ganguly, Ramakrishna Nemani, Shreekant Gayaka
To this end, we first derive the size of the feature space for some standard textural features extracted from the input dataset and then use the theory of Vapnik-Chervonenkis dimension to show that hand-crafted feature extraction creates low-dimensional representations which help in reducing the overall excess error rate.
no code implementations • 29 Oct 2015 • Chris Alvin, Sumit Gulwani, Rupak Majumdar, Supratik Mukhopadhyay
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 geometric figure together with a set of properties true of it.
1 code implementation • 11 Sep 2015 • Saikat Basu, Sangram Ganguly, Supratik Mukhopadhyay, Robert DiBiano, Manohar Karki, Ramakrishna Nemani
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning.
Ranked #2 on Satellite Image Classification on SAT-6
no code implementations • 11 Sep 2015 • Saikat Basu, Manohar Karki, Sangram Ganguly, Robert DiBiano, Supratik Mukhopadhyay, Ramakrishna Nemani
Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem.