Education: Post-Doc from RWTH Aachen, Germany and PhD in Computer Science from Thapar Institute of Engineering and Technology, Patiala, India 

Research Interests: Pattern Recognition and Machine Learning

RESEARCH OVERVIEW

• In machine learning, I work in classification and deep learning techniques. (published in journals/ conf as PMLR, JMLC)

• In pattern recognition, I work in document analysis and recognition to recognize online/ offline handwritten text.  (published in journals/ conf as IJDAR, ICDAR)

• I work in algorithmic and code development for optimization problems such as assignment or transportation problems. (published in journals as EJOR, AMM)

SELECTED PUBLICATIONS

2024

• V. K. Chauhan, S. Singh and Anuj Sharma, “HCR-Net: A deep learning based script independent handwritten character recognition network”, Multimedia Tools and Applications, Springer, 2024 paper

• S. Kaur, E. Jain, Anuj Sharma, K. Dahiya, "An efficient algorithm for two-stage capacitated time minimization transportation problem with restricted flow", RAIRO - Operations Research, Springer, 2024 paper

• L. Kumari, S. Singh, VVS Rathore and Anuj Sharma, "GatedLexiconNet: A Comprehensive End-to-End Handwritten Paragraph Text Recognition System", arXiv:2404.14062   paper

• S. Singh, Anuj Sharma and V. K. Chauhan, “GTAGCN: Generalized Topology Adaptive Graph Convolutional Networks”, arXiv:2403.15077   paper

• S. Singh, S Rohilla and Anuj Sharma, "An inclusive review on deep learning techniques and their scope in handwriting recognition", arXiv:2404.08011 paper

2023

• U. Thakur and Anuj Sharma, "Offline Handwritten Mathematical Recognition using Adversarial Learning and Transformers", International Journal of Document Analysis and Recognition (IJDAR), Springer, 2023 paper 

• S. Singh, V. K. Chauhan and Anuj Sharma, "Indic Script Family and Its Offline Handwriting Recognition for Characters/ Digits and Words: A Comprehensive Survey", Artificial Intelligence Review, Springer, 2023 paper

• L. Kumari, S. Singh, VVS Rathore and Anuj Sharma, "A Comprehensive Handwritten Paragraph Text Recognition System: LexiconNet", Workshop on Machine Learning, International Conference on Document Analysis and Recognition (ICDAR), Lecture Notes in Computer Science (LNCS), 2023 paper

• Anuj Sharma, S. Singh and S. Ratna, "Graph Neural Network Operators: a Review", Multimedia Tools and Applications, Springer, 2023 paper

2022

• • L. Kumari, S. Singh, VVS Rathore and Anuj Sharma, "A Lexicon and Depth-wise Separable Convolution Based Handwritten Text Recognition System ", Proceedings of IVCNZ 2022 (an IAPR conference), Lecture Notes in Computer Science (LNCS), Springer, 2022  paper

  • E. Jain, K. Dahiya, Anuj Sharma and V. Verma, "Task preference-based bottleneck assignment problem", Computational and Applied Mathematics, Springer, 2022  paper

  • F. Xie, Anuj Sharma and Z. Li, "An alternate approach to solve two-level priority based assignment problem", Computational Optimization and Applications, vol. 81, pp. 613-656, Springer, 2022  paper 

  • L. Kumari, S. Singh, VVS Rathore and Anuj Sharma, "Lexicon and attention based handwritten text recognition system", Machine Graphics and Vision, 31(1/4), 75–92, 2022  paper

  • Charanjeet and Anuj Sharma,  "A Review of Online Supervised Learning", Evolving Systems, Springer, 2022 paper

  • L. Kumari, S. Singh and Anuj Sharma, "Page Level Input for Handwritten Text Recognition in Document Images", In proceedings of 7th ICHSA, Seoul, Lecture Notes on Data Engineering and Communications Technologies, Springer 2022  paper

  • Charanjeet and Anuj Sharma, "Online Newton step based on pseudo inverse and elementwise multiplication", In proceedings of 7th ICHSA, Seoul, Lecture Notes on Data Engineering and Communications Technologies, Springer, 2022  paper

  • Patent number: 2021103042, "A System and Method for Predicting Badminton Match Outcome", Inventors: M. Sharma, Naresh Kumar, Monika, P. Kumar, N. Kumar, Anuj Sharma, A.   Kumar, Anil Kumar, I. Bhutani, IP Australia, 2022 

2021

• • L. Kumari and Anuj Sharma, "A Review of Deep Learning Techniques in Document Image Word Spotting",  Archives of Computational Methods in Engineering, vol. 29, pp. 1085-1106, Springer, 2021 paper

  • V. K. Chauhan, Anuj Sharma, K. Dahiya, "LIBS2ML: A library for scalable second order machine learning algorithms",  Software Impacts, vol. 10, Elsevier, 2021 paper

  • U. Thakur and Anuj Sharma, “Newton methods based convolution neural networks using parallel processing”, arXiv:2112.01401, 2021  paper

  • S. Singh, Anuj Sharma and V. K. Chauhan, “Online handwritten Gurmukhi word recognition using fine-tuned Deep Convolutional Neural Network on offline features”, Machine Learning with Applications, vol. 5, Elsevier, 2021 paper 

2020

• • V. K. Chauhan, Anuj Sharma and K. Dahiya, "Stochastic Trust Region Inexact Newton Method for Large-scale Machine Learning", International Journal of Machine Learning and Cybernetics, vol. 11, pp. 1541–1555, Springer, 2020 paper  

  • P. Kaur, Anuj Sharma, V. Verma and K. Dahiya, "An alternate approach to solve two-level hierarchical time minimization transportation problem", 4OR, vol. 20, pp. 23-61, Springer, 2020 paper

  • J. Kaur, S. Singh and Anuj Sharma, "Dynamic features based stroke recognition system for signboard images of Gurmukhi text", Multimedia Tools and Applications, vol. 80, pp. 665–689, Springer, 2020 paper

  • Charanjeet and Anuj Sharma, "Modified online Newton step based on element wise multiplication", Computational Intelligence, vol. 36 (3), pp. 1010-1025, Wiley, 2020 paper

  • Charanjeet and Anuj Sharma, "Online learning using multiple times weight updating", Applied Artificial Intelligence, vol. 34 (6), pp. 515-536, Taylor and Francis, 2020 paper

  • S. Rohilla, Anuj Sharma and R. K. Singla, "Role of Sub-trajectories in Online Signature Verification", Array, vol. 6, Elsevier, 2020  paper

2019

• • S. Singh and Anuj Sharma, “Online Handwritten Gurmukhi Words Recognition: An Inclusive Study ”, ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), vol. 18(3), pp. 21:1-21:55, ACM, 2019 paper

  • V. K. Chauhan, K. Dahiya and Anuj Sharma, "SAAGs: Biased Stochastic Variance Reduction Methods for Large-scale Learning", Applied Intelligence, vol. 49(9), pp 3331–3361, Springer, 2019 paper

  • E. Jain, K. Dahiya, Anuj Sharma and V. Verma, "An improved algorithm for two stage time minimization assignment problem", Journal of Combinatorial Optimization, vol. 37, pp. 713-736, Springer, 2019 paper

  • J. Kaur, S. Singh and Anuj Sharma, "Recognition of Gurmukhi signboard image classes based on static and dynamic feature sets ", 7th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2019), Springer  paper

  • S. Rohilla, Anuj Sharma and R. K. Singla, "Mobile Based Signature Database (MOBSIGN DB): A new signature database ", International Conference on “Advanced Communication & Computational Technology (ICACCT-2019), Springer  paper

  • S. Singh and Anuj Sharma, "Recognition of online handwritten Gurmukhi characters through neural networks",  International Conference on “Advanced Communication & Computational Technology (ICACCT-2019), Springer   paper

  • Charanjeet, S. Singh and Anuj Sharma, "A comparative analysis on Online Handwritten Stroke Classification using online learning", International Conference on “Advanced Communication & Computational Technology (ICACCT-2019), Springer  paper

2018

• • V. K. Chauhan, K. Dahiya and Anuj Sharma, "Problem Formulations and Solvers in Linear SVM - a Review", Artificial Intelligence Review, vol. 52, pp. 803-855, Springer, 2019 paper    

  • V. K. Chauhan, Anuj Sharma and K. Dahiya, "Faster Learning by Reduction of Data Access Time", Applied Intelligence, vol. 48, no. 12, pp. 4715-4729, Springer, 2018 paper 

  • A. Kumar, Anuj Sharma and R. K. Singla, "An Efficient License Plate Extraction Technique”, Proc. on RACCCS, Advances in Intelligent Systems and Computing, (a chapter), pp. 487-495, Springer, 2018 paper 

2017

• • V. K. Chauhan, K. Dahiya and Anuj Sharma, "Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems", Proceedings of Machine Learning Research (PMLR), vol. 77, pp. 49-64, 2017 paper

  • S. Rohilla, Anuj Sharma and R. K. Singla, “Optimal Feature Set Selection in Online Signature Verification”, Int. J. Biometrics, vol. 9(4), pp. 319-346, 2017 paper

  • S. Singh, Anuj Sharma and I. Chhabra, “A Dominant Points based Feature Extraction Approach to Recognize Online Handwritten Strokes”, International Journal of Document Analysis and Recognition (IJDAR), vol. 20(1), pp. 37-58, Springer, 2017 paper

  • S. Rohilla and Anuj Sharma, “SVM based Online Signature Verification Technique using Reference Feature Vector”, Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, vol. 87(1), pp. 125-136, Springer, 2017  paper

  • V. K. Chauhan, K. Dahiya and Anuj Sharma, "Trust Region Levenberg-Marquardt Method for Linear SVM", Proceedings of the Ninth International Conference on Advances in Pattern Recognition (ICAPR-2017), Indian Statistical Institute, Bangalore paper 

2016

• • P. Kaur, Anuj Sharma, V. Verma and K. Dahiya, "A priority based assignment problem", Applied Mathematical Modelling, vol. 40, no. 17-18, pp. 7784-7795, Elsevier, 2016 paper   

  • S. Singh, Anuj Sharma and I. Chhabra, “Online Handwritten Gurmukhi Strokes Dataset based on Minimal Set of Words”, ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), vol. 16(1), ACM, 2016 paper 

  • K. Dahiya, V. K. Chauhan and Anuj Sharma, "Online Support Vector Machine Based on Minimum Euclidean Distance”, Proc. on CVIP, Advances in Intelligent Systems and Computing, (a chapter), pp. 89-99, Springer, 2016 paper

till 2015

• • Anuj Sharma, P. Kaur, K. Dahiya and V. Verma, “An iterative algorithm for two level hierarchical time minimization transportation problem”, European Journal of Operational Research, vol. 246, no. 3, pp. 700-707, Elsevier, 2015  paper    

  • Anuj Sharma, "A Combined Static and Dynamic Feature Extraction Technique to recognize handwritten digits", Viet. Journal of Comp. Sc., vol. 2 (3), pp. 133-142, Springer, 2015  paper  (now journal with world scientific)   

  • R. Kumar, R. K. Sharma and Anuj Sharma, “Recognition of Multi-Stroke Based Online Handwritten Gurmukhi Aksharas”, Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, vol. 85, no. 1, pp. 159-168, 2015, Springer   paper

  • S. Rohilla, Anuj Sharma and R. K. Singla, "Online Signature Verification at Sub-trajectory Level", Proc. of ICACNI, Advanced Computing, Networking and Informatics in series of Smart Innovation, Systems and Technologies, (a chapter) Springer, Vol. 28, pp. 369-374, 2014  paper

  • K, Dahiya and Anuj Sharma, "Reducing Neural Network Training Data using Support Vectors", In IEEE proceedings of RAECS, 2014  paper

  • Anuj Sharma, “Recovery of Drawing order in Handwritten Digit Images”, In IEEE proceedings of ICIIP, 2013, pp 437-441  paper 

  • Anuj Sharma, R. Kumar and R. K. Sharma, "HMM Based Online Handwritten Gurmukhi Character Recognition", International Journal of Machine Graphics and Vision, vol. 19, no. 4, pp. 439-449, 2010  paper    

  • Anuj Sharma, R. Kumar and R. K. Sharma, "Rearrangement of Strokes in Recognition of Online Handwritten Gurmukhi Words", In IEEE Proceedings of 10th International Conference on Document Analysis and Recognition, Barcelona, Spain (ICDAR), pp. 1241-1245, 2009.  paper

  • Anuj Sharma, R. Kumar and R. K. Sharma, "Online preprocessing of handwritten Gurmukhi strokes ", International Journal of Machine Graphics and Vision,  Polish Academy of Sciences, Vol. 18, no. 1, pp. 105-120, 2009   paper  

  • Anuj Sharma, R. Kumar and R. K. Sharma, "Online Handwritten Gurmukhi Character Recognition using Elastic Matching", IEEE proceedings of International Congress on Image and Signal Processing (CISP), Sanya, vol. 2, pp. 391-396, 2008.  paper