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ORCIDDeepak Mittal
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2020 – today
- 2024
[i8]Debarpan Bhattacharya, Amir H. Poorjam, Deepak Mittal, Sriram Ganapathy:
Gradient-free Post-hoc Explainability Using Distillation Aided Learnable Approach. CoRR abs/2409.11123 (2024)- 2023
- [c13]Deepak Mittal:
Design a Gated PMOS Spillage Reduction Approach for CMOS SRAM Cell in 90nm Technology Node. ICCCNT 2023: 1-4 - [c12]Deepak Mittal:
SRAM Cell Leakage Reduction Methodologies for Low Leakage Cache Memories. ICCCNT 2023: 1-5 - [i7]Harika Abburi, Tanya Chaudhary, Haider Ilyas, Lakshmi Manne, Deepak Mittal, Don Williams, Derek Snaidauf, Edward Bowen, Balaji Veeramani:
A Closer Look at Bearing Fault Classification Approaches. CoRR abs/2309.17001 (2023) - 2022
- [c11]Deepak Mittal:
Performance Analysis of Various CMOS SRAM Cells. ICCCNT 2022: 1-5 - [c10]Arjit Jain, Pranay Reddy Samala, Deepak Mittal, Preethi Jyothi, Maneesh Singh:
SPLICEOUT: A Simple and Efficient Audio Augmentation Method. INTERSPEECH 2022: 2678-2682 - [c9]Debottam Dutta, Debarpan Bhattacharya, Sriram Ganapathy, Amir Hossein Poorjam, Deepak Mittal, Maneesh Singh:
Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 Detection. INTERSPEECH 2022: 2863-2867 - [i6]Deepak Mittal, Amir H. Poorjam, Debottam Dutta, Debarpan Bhattacharya, Zemin Yu, Sriram Ganapathy, Maneesh Kumar Singh:
Svadhyaya system for the Second Diagnosing COVID-19 using Acoustics Challenge 2021. CoRR abs/2206.05462 (2022) - [i5]Debottam Dutta, Debarpan Bhattacharya, Sriram Ganapathy, Amir H. Poorjam, Deepak Mittal, Maneesh Kumar Singh:
Interpretable Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 Detection. CoRR abs/2206.13365 (2022) - 2021
- [c8]Arjit Jain, Pranay Reddy Samala, Preethi Jyothi, Deepak Mittal, Maneesh Kumar Singh:
Perturb, Predict & Paraphrase: Semi-Supervised Learning using Noisy Student for Image Captioning. IJCAI 2021: 758-764 - [c7]Flávio Ávila, Amir H. Poorjam, Deepak Mittal, Charles Dognin, Ananya Muguli
, Rohit Kumar, Srikanth Raj Chetupalli, Sriram Ganapathy, Maneesh Singh:
Investigating Feature Selection and Explainability for COVID-19 Diagnostics from Cough Sounds. Interspeech 2021: 951-955 - [i4]Arjit Jain, Pranay Reddy Samala, Deepak Mittal, Preethi Jyothi, Maneesh Singh:
SpliceOut: A Simple and Efficient Audio Augmentation Method. CoRR abs/2110.00046 (2021) - 2020
- [c6]V. S. R. Veeravasarapu, Abhishek Goel, Deepak Mittal, Maneesh Kumar Singh:
ProAlignNet: Unsupervised Learning for Progressively Aligning Noisy Contours. CVPR 2020: 9668-9676 - [c5]Deepak Mittal, V. K. Tomar:
Performance Evaluation of 6T, 7T, 8T, and 9T SRAM cell Topologies at 90 nm Technology Node. ICCCNT 2020: 1-4 - [i3]V. S. R. Veeravasarapu, Abhishek Goel, Deepak Mittal, Maneesh Kumar Singh:
ProAlignNet : Unsupervised Learning for Progressively Aligning Noisy Contours. CoRR abs/2005.11546 (2020)
2010 – 2019
- 2019
- [j1]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Studying the plasticity in deep convolutional neural networks using random pruning. Mach. Vis. Appl. 30(2): 203-216 (2019) - 2018
- [c4]Deepak Mittal, Avinash Reddy, Gitakrishnan Ramadurai, Kaushik Mitra, Balaraman Ravindran:
Training a deep learning architecture for vehicle detection using limited heterogeneous traffic data. COMSNETS 2018: 589-294 - [c3]Deepak Mittal, Amit Niranjan:
Designing of Multiplexer and De-Multiplexer Using Different Adiabatic Logic in 90nm Technology. ICCCNT 2018: 1-7 - [c2]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks. WACV 2018: 848-857 - [i2]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks. CoRR abs/1801.10447 (2018) - [i1]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning. CoRR abs/1812.10240 (2018) - 2014
- [c1]Apoorv Agarwal, Ankit Agarwal, Deepak Mittal:
An Error Analysis Tool for Natural Language Processing and Applied Machine Learning. COLING (Demos) 2014: 1-5
Coauthor Index
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