Theses

1. Learning to Super-Resolve Images Using Self-Similarities
   Abhishek Singh
   Ph.D. Dissertation, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Feb 2015.
   
   
2. Cost Functions For Supervised Learning Based on a Robust Similarity Metric 
   Abhishek Singh
   M.S. Thesis, Department of Electrical and Computer Engineering, University of Florida, Gainesville. May 2010.

Book Chapter

1. Algorithms for Entropy and Correntropy Adaptation with Applications to Linear Systems
   Deniz Erdogmus, Seungju Han and Abhishek Singh 
   Chapter 4, Information Theoretic Learning: Renyi's Entropy and Kernel Perspectives. Jose C. Principe. Springer 2010.

Journal Articles

1. Simultaneous Super-Resolution and Denoising of Natural Images
   Abhishek Singh, Fatih Porikli and Narendra Ahuja
   IEEE Transactions on Pattern Analysis and Machine Intelligence. (submitted)
   
   
2. Learning Ramp Transformation for Single Image Super-Resolution
   Abhishek Singh and Narendra Ahuja
   Computer Vision and Image Understanding, 2015
   
   
3. The C-Loss Function for Pattern Classification
   Abhishek Singh and Jose Principe
   Pattern Recognition, vol. 47, issue 1, pp. 441-453, Jan 2014.
   
   
4. Information Theoretic Learning with Adaptive Kernels
   Abhishek Singh and Jose Principe
   Signal Processing, vol. 91, issue 2, pp. 203-213, Feb 2011.
   Listed among Most Viewed Articles of the journal
   
   
5. Segmentation of Remotely Sensed Images Using Resampling Based Bayesian Learning
   Abhishek Singh, Padmini Jaikumar and Suman K. Mitra
   Journal of Pattern Recognition Research, vol. 5, no. 1, pp. 119-130, 2010.

Conference Proceedings

1. Single Image Super-Resolution Using Transformed Self-Exemplars
   Jia-Bin Huang, Abhishek Singh and Narendra Ahuja
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015)
   
   
2. Super-Resolution Using Sub-Band Self-Similarity
   Abhishek Singh and Narendra Ahuja
   Asian Conference on Computer Vision (ACCV 2014)
   
   
3. Super-Resolving Noisy Images
   Abhishek Singh, Fatih Porikli and Narendra Ahuja
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014)
   
   
4. Sub-band Energy Constraints for Self-Similarity Based Super-Resolution
   Abhishek Singh and Narendra Ahuja
   International Conference on Pattern Recognition (ICPR 2014)
   
   
5. Single Image Super-Resolution Using Adaptive Domain Transformation
   Abhishek Singh and Narendra Ahuja
   IEEE International Conference on Image Processing (ICIP 2013)
   
   
6. On Stochastic Gradient Descent and Quadratic Mutual Information for Multimodal Image Registration
   Abhishek Singh and Narendra Ahuja
   IEEE International Conference on Image Processing (ICIP 2013)
   
   
7. Exploiting Ramp Structures for Improving Optical Flow Estimation
   Abhishek Singh and Narendra Ahuja
   International Conference on Pattern Recognition (ICPR 2012)
   
   
8. Online Learning With Kernels: Overcoming the Growing Sum Problem
   Abhishek Singh, Narendra Ahuja and Pierre Moulin
   IEEE Workshop on Machine Learning for Signal Processing (MLSP 2012)
   
   
9. A Variational Approach for Optimizing Quadratic Mutual Information for Medical Image Registration
   Abhishek Singh, Ying Zhu and Christophe Chefd'hotel
   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)
   
   
10. A Loss Function for Classification Based on a Robust Similarity Metric
    Abhishek Singh and Jose Principe
    International Joint Conference on Neural Networks (IJCNN 2010)
    
    
11. Realistic and efficient 2D crack simulation
    Jacob Yadegar, Xiaoqing Liu and Abhishek Singh. 
    SPIE International Conference on Defense, Security, and Sensing, 2010.
      
12. Hidden Markov Models for Modeling Blood Pressure Data to Predict Acute Hypotension
    Abhishek Singh, Tejaswi Tamminedi, Guy Yosiphon, Anurag Ganguli and Jacob Yadegar. 
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)
    
    
13. Kernel Width Adaptation in Information Theoretic Cost Functions
    Abhishek Singh and Jose Principe
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)
    
    
14. A Closed Form Recursive Solution for Maximum Correntropy Training
    Abhishek Singh and Jose C. Principe 
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)
    
    
15. Using Correntropy as a Cost Function in Linear Adaptive Filters
    Abhishek Singh and Jose C. Principe
    IEEE International Joint Conference on Neural Networks (IJCNN 2009)
    
    
16. Efficient Learning of Finite Mixture Densities using Mutual Information
    Padmini Jaikumar, Abhishek Singh and Suman K. Mitra
    International Conference on Advances in Pattern Recognition (ICAPR 2009)
    
    
17. A Sampling-Resampling Based Bayesian Learning Approach for Object Tracking
    Abhishek Singh, Padmini Jaikumar and Suman K. Mitra
    Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2008)
    Best Paper Award in IEEE Region 10 (Asia-Pacific) Student Paper Contest 2008
    
    
18. A Bayesian Learning Approach for Clustering of Satellite Images
    Abhishek Singh, Padmini Jaikumar and Suman K. Mitra
    Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2008)
    
    
19. Background Subtraction in Videos Using Bayesian Learning with Motion Information
    Padmini Jaikumar, Abhishek Singh and Suman K. Mitra
    British Machine Vision Conference (BMVC 2008)
    
    
20. Detection and Tracking of Objects in Low Contrast Conditions
    Abhishek Singh, Padmini Jaikumar, Suman K. Mitra, Manjunath V. Joshi and Asim Banerjee
    National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2008)