Publications

(Graduate student co-authors are marked with *, undergraduate student co-authors are marked with ** ) 

Book Chapters

• J. Chandra, M. Rangaswamy, B. Banerjee, A. Prajapati*, Z. Akhtar, K. Sakauye and A. Joseph*. (2022) "Applications of artificial intelligence to neurological disorders: Current technologies and open problems", Augmenting Neurological Disorder Prediction and Rehabilitation using Artificial Intelligence, A. Pillai and B. Menon, Editors, Elsevier, Chapter 12, pp. 243–272.

• B. Chandrasekaran, B. Banerjee, U. Kurup, J. R. Josephson and R. Winkler. (2009) "Diagrammatic reasoning in army situation understanding and planning: Architecture for decision support and cognitive modeling", Advanced Decision Architectures for the Warfighter: Foundations and Technology, P. McDermott and L. Allender, Editors, Chapter 21, pp. 379–394.

• B. Banerjee and B. Chandrasekaran. (2007) "A constraint satisfaction framework for visual problem solving", Trends in Constraint Programming, F. Benhamou, N. Jussien and B. O’Sullivan, Editors, Hermes Science, Chapter 26.

Journal Articles

• B. Banerjee and M. Baruah*. (2024) "Attention-based variational autoencoder models for human–human interaction recognition via generation", Sensors, Vol. 24, Issue 12, pp. 3922.

• M. Baruah*, B. Banerjee and A. K. Nagar. (2023) "Intent prediction in human–human interactions", IEEE Transactions on Human-Machine Systems, Vol. 53, Issue 2, pp. 458–463.

• M. Baruah*, B. Banerjee, A. K. Nagar and R. Marois. (2023) "AttentionMNIST: A mouse-click attention tracking dataset for handwritten numeral and alphabet recognition", Scientific Reports, Nature, Vol. 13, Article 3305. Dataset: https://github.com/Murchana/AttentionMNIST .

• D. P. Kaur, N. P. Singh and B. Banerjee. (2022) "A review of platforms for simulating embodied agents in 3D virtual environments", Artificial Intelligence Review, Springer Nature.

• M. Baruah*, B. Banerjee and A. K. Nagar. (2022) "An attention-based predictive agent for static and dynamic environments", IEEE Access, Vol. 10, pp. 17310–17317.

• M. H. Kapourchali* and B. Banerjee. (2020) "State estimation via communication for monitoring", IEEE Transactions on Emerging Topics in Computational Intelligence, Vol. 4, Issue 6, pp. 786–793.

• J. K. Dutta* and B. Banerjee. (2019) "Improved outlier detection using sparse coding-based methods", Pattern Recognition Letters, Elsevier, Vol. 122, pp. 99–105. 

• S. Najnin* and B. Banerjee. (2019) "Speech recognition using cepstral articulatory features", Speech Communication, Elsevier, Vol. 107, pp. 26–37.

• M. H. Kapourchali* and B. Banerjee. (2018) "Unsupervised feature learning from time-series data using linear models", IEEE Internet of Things Journal, Vol. 5, Issue 5, pp. 3918-3926.

• S. Najnin* and B. Banerjee. (2018) "Pragmatically framed cross-situational noun learning using computational reinforcement models", Frontiers in Psychology (Cognitive Science section), James L. McClelland, Editor, Volume 9, Article 5.

• S. Najnin* and B. Banerjee. (2017) "A predictive coding framework for a developmental agent: Speech motor skill acquisition and speech production", Speech Communication, Elsevier, Vol. 92, pp. 24–41.

• L. L. Mendel, S. Lee*, M. Pousson, C. Patro*, S. McSorley*, B. Banerjee, S. Najnin* and M. H. Kapourchali*. (2017) "Corpus of deaf speech for acoustic and speech production research", Journal of the Acoustical Society of America, Vol. 142, No. 1, pp. EL102-EL107.

• J. K. Dutta*, B. Banerjee and C. K. Reddy. (2016) "RODS: Rarity based outlier detection in a sparse coding framework", IEEE Transactions on Knowledge and Data Engineering, Vol. 28, Issue 2, pp. 483-495.

• S. Najnin* and B. Banerjee. (2015) "Improved speech inversion using general regression neural network", Journal of the Acoustical Society of America, Vol. 138, No. 3, pp. EL229-EL235.

• B. Banerjee and J. K. Dutta*. (2014) "SELP: A general-purpose framework for learning the norms from saliencies in spatiotemporal data", Neurocomputing: Special Issue on Brain Inspired Models of Cognitive Memory, Elsevier, Vol. 138, pp. 41–60.

• B. Banerjee and B. Chandrasekaran. (2013) "A framework of Voronoi diagram for planning multiple paths in free space", Journal of Experimental & Theoretical Artificial Intelligence, Taylor & Francis, Vol. 25, Issue 4, pp. 457–475.

• B. Chandrasekaran, B. Banerjee, U. Kurup and O. Lele. (2011) "Augmenting cognitive architectures to support diagrammatic imagination", Topics in Cognitive Science: Special Issue on Modeling Spatial Cognition, G. Gunzelmann, Editor, Cognitive Science Society, Vol. 3, Issue 4, pp. 760–777, October.

• B. Banerjee and B. Chandrasekaran. (2010) "A constraint satisfaction framework for executing perceptions and actions in diagrammatic reasoning", Journal of Artificial Intelligence Research, Vol. 39, pp. 373–427.

• B. Banerjee. (2007) "String tightening as a self-organizing phenomenon", IEEE Transactions on Neural Networks, Vol. 18, No. 5, pp. 1463–1471.

• B. Banerjee. (2006) "A layered abductive inference framework for diagramming group motions", Special Issue of Logic Journal of IGPL: Abduction, Practical Reasoning, and Creative Inferences in Science, L. Magnani, Editor, Vol. 14, No. 2, pp. 363–378, Oxford University Press.

• B. Banerjee. (2004) "Recognition of partially occluded shapes using a neural optimization network", Machine Graphics & Vision, Institute of Computer Science of the Polish Academy of Sciences, Vol. 13, No. 1/2, pp. 3–23.

• B. Banerjee. (2003) "A self-organizing auto-associative network for the generalized physical design of microstrip patches", IEEE Transactions on Antennas & Propagation, Vol. 51, No. 6, pp. 1301–1306.

Conference/Symposium Papers

• B. Banerjee and M. Baruah*. (2023) "An attention-based predictive agent for handwritten numeral/alphabet recognition via generation", NeurIPS 2023 Workshop on Gaze Meets ML, December 16, New Orleans, LA. [Best Paper Award] Appears in Proceedings of Machine Learning Research, Vol. 226, pp. 4–20, 2024.

• M. Baruah* and B. Banerjee. (2022) "Speech emotion recognition via generation using an attention-based variational recurrent neural network", INTERSPEECH, pp. 4710-4714, September 18-22, Incheon, Korea.

• A. Prajapati* and B. Banerjee. (2022) "Simulating distributed wireless sensor networks for edge-AI", Conference on Cloud and Internet of Things, March 28-30, Marrakech, Morocco.

• B. Banerjee, M. H. Kapourchali*, M. Baruah*, M. Deb*, K. Sakauye and M. Olufsen. (2021) "Synthesizing skeletal motion and physiological signals as a function of a virtual human’s actions and emotions", SIAM International Conference on Data Mining, April 29-May 1. [Acceptance rate 85/400=21.25%] 

• M. Baruah* and B. Banerjee. (2020) "Modality selection for classification on time-series data", In MileTS ’20: 6th KDD (ACM SIGKDD International Conference on Knowledge Discovery and Data Mining) Workshop on Mining and Learning from Time Series, August 24, San Diego, CA.

• M. Baruah* and B. Banerjee. (2020) "The perception-action loop in a predictive agent", CogSci 2020: 42nd Annual Meeting of the Cognitive Science Society, pp. 1171-1177, July 29-August 1.

• M. Baruah* and B. Banerjee. (2020) "A multimodal predictive agent model for human interaction generation", CVPR (IEEE/CVF Conference on Computer Vision and Pattern Recognition) Precognition Workshop, June 14-19.

• M. H. Kapourchali* and B. Banerjee. (2020) "EPOC: Efficient perception via optimal communication", Thirty-Fourth AAAI Conference on Artificial Intelligence, pp. 4107-4114, February 7-12, New York, NY. [Acceptance rate 1591/7737=20.56%]

• Z. Akhtar, D. Dasgupta and B. Banerjee. (2019) "Face authenticity: An overview of face manipulation generation, detection and recognition", International Conference on Communication and Information Processing, May 17-18, Pune, India.

• M. H. Kapourchali* and B. Banerjee. (2018) "Multiple heads outsmart one: A computational model for distributed decision making", CogSci 2018: 40th Annual Meeting of the Cognitive Science Society, pp. 1776-1781, July 25-28, Madison, WI.

• J. K. Dutta* and B. Banerjee. (2017) "Variation in classification accuracy with number of glimpses", International Joint Conference on Neural Networks, pp. 447-453, May 14-19, Anchorage, AK.

• A. K. Sadhu*, A. Konar, B. Banerjee and A. Nagar. (2017) "Multi-robot cooperative planning by consensus Q-learning", International Joint Conference on Neural Networks, pp. 4158-4164, May 14-19, Anchorage, AK.

• R. Lahiri*, S. Saha*, A. Konar, B. Banerjee and A. Nagar. (2017) "HMM-based gesture recognition system using Kinect sensor for improvised human-computer interaction", International Joint Conference on Neural Networks, pp. 2776-2783, May 14-19, Anchorage, AK.

• B. Banerjee, M. H. Kapourchali*, S. Najnin*, L. L. Mendel, S. Lee*, C. Patro* and M. Pousson. (2016) "Inferring hearing loss from learned speech kernels", IEEE International Conference on Machine Learning and Applications, pp. 26-31, December 18-20, Anaheim, CA. [Acceptance rate 24.69%]

• S. Najnin* and B. Banerjee. (2016) "Emergence of vocal developmental sequences in a predictive coding model of speech acquisition", INTERSPEECH, pp. 1113-1117, September 8-12, San Francisco, CA.

• S. Najnin*, B. Banerjee, L. L. Mendel, M. H. Kapourchali*, J. K. Dutta*, S. Lee*, C. Patro* and M. Pousson. (2016) "Identifying hearing loss from learned speech kernels", INTERSPEECH, pp. 243-247, September 8-12, San Francisco, CA.

• S. Saha*, R. Lahiri*, A. Konar, B. Banerjee and A. Nagar. (2016) "Human skeleton matching for e-learning of dance using a probabilistic neural network", International Joint Conference on Neural Networks, pp. 1754-1761, July 25-29, Vancouver, Canada.

• S. Saha*, A. Konar, A. Saha*, A. K. Sadhu*, B. Banerjee and A. Nagar. (2016) "EEG based gesture mimicking by an artificial limb using cascade-correlation learning architecture", International Joint Conference on Neural Networks, pp. 4680-4687, July 25-29, Vancouver, Canada.

• A. Panda**, S. Ghoshal**, A. Konar, B. Banerjee and A. Nagar. (2016) "Static learning particle swarm optimization with enhanced exploration and exploitation using adaptive swarm size", IEEE Congress on Evolutionary Computation, pp. 1869-1876, July 25-29, Vancouver, Canada.

• S. Saha*, S. Datta*, A. Konar, B. Banerjee and A. Nagar. (2016) "A novel gesture recognition system based on fuzzy logic for healthcare applications", IEEE International Conference on Fuzzy Systems, pp. 634-641, July 25-29, Vancouver, Canada.

• J. K. Dutta* and B. Banerjee. (2015) "Online detection of abnormal events using incremental coding length", Twenty-Ninth AAAI Conference on Artificial Intelligence, pp. 3755-3761, January 25-29, Austin, TX. [Acceptance rate 531/1991=26.7%]

• B. Banerjee and K. G. Dizaji*. (2014) "Unsupervised learning of spatial transformations in the absence of temporal continuity", IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing, pp. 82–89, December 9-12, Orlando, FL.

• J. K. Dutta*, B. Banerjee, R. Ilin and R. Kozma. (2014) "Abnormal event detection in EEG imaging – Comparing predictive and model-based approaches", IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, pp. 10–15, December 9-12, Orlando, FL.

• J. K. Dutta* and B. Banerjee. (2014) "Learning features and their transformations from natural videos", IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, pp. 55–61, December 9-12, Orlando, FL.

• B. Banerjee. (2013) "How can the blind men see the elephant?", AAAI Fall Symposium on How Should Intelligence be Abstracted in AI Research, Technical Report FS-13-02, pp. 2–8, November 15-17, Arlington, VA.

• J. K. Dutta* and B. Banerjee. (2013) "Learning features and their transformations by spatial and temporal spherical clustering", Computing Research Repository arXiv:cs.NE (Neural and Evolutionary Computing) 1308.2350.

• B. Banerjee and J. K. Dutta*. (2013) "A predictive coding framework for learning to predict changes in streaming data", IEEE ICDM Workshops (Incremental Clustering, Concept Drift and Novelty Detection), pp. 497–504, December 7-10, Dallas, TX.

• B. Banerjee and J. K. Dutta*. (2013) "An online clustering algorithm that ignores outliers: Application to hierarchical feature learning from sensory data", IEEE ICDM Workshops (Incremental Clustering, Concept Drift and Novelty Detection), pp. 505–512, December 7-10, Dallas, TX.

• B. Banerjee and J. K. Dutta*. (2013) "Efficient learning from explanation of prediction errors in streaming data", IEEE BigData Conference, pp. 14–20, October 6-9, Santa Clara, CA.

• B. Banerjee and J. K. Dutta*. (2013) "Hierarchical feature learning from sensorial data by spherical clustering", IEEE BigData Conference, pp. 7–13, October 6-9, Santa Clara, CA.

• B. Banerjee and B. Chandrasekaran. (2010) "A spatial search framework for executing perceptions and actions in diagrammatic reasoning", Diagrams 2010 - 6th Intl. Conf. on the Theory and Application of Diagrams, Portland, OR. Appears in Diagrammatic Representation and Inference, A. K. Goel, M. Jamnik and N. H. Narayanan, Editors, Lecture Notes in Artificial Intelligence 6170, Springer, Heidelberg, pp. 144-159. [Acceptance rate 14/70=20%]

• B. Banerjee and B. Chandrasekaran. (2007) "Representations and strategies for solving spatial problems with diagrams", Proc. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pp. 183-188, Coeur d'Alène, ID. [Acceptance rate 30%]

• B. Banerjee and B. Chandrasekaran. (2006) "A framework for planning multiple paths in free space", Proc. 25th Army Science Conf., Orlando, FL.

• B. Banerjee and B. Chandrasekaran. (2006) "On automating perceptions and actions in reasoning with military diagrams", Proc. 25th Army Science Conf., Orlando, FL.

• B. Banerjee and B. Chandrasekaran. (2006) "A spatial constraint satisfaction framework for synthesizing perceptions and actions in diagrammatic reasoning", Proc. 1st Intl. Workshop on Constraint Programming for Graphical Applications. In conjunction with CP-2006 - 12th Intl. Conf. on Principles & Practice of Constraint Programming, Nantes, France. (An extended version of this paper was published as a book chapter in 2007.)

• B. Chandrasekaran, U. Kurup and B. Banerjee. (2005) "A diagrammatic reasoning architecture: design, implementation and experiments", AAAI Spring Symp. on Reasoning with Mental and External Diagrams: Computational Modeling and Spatial Assistance, Stanford University, CA.

• B. Banerjee. (2004) "Using abduction for diagramming group motions", MBR’04 - Intl. Conf. on Model-Based Reasoning in Science and Engineering: Abduction, Visualization, and Simulation, University of Pavia, Italy. (An extended version of this paper was published as a journal article in 2006.)

• B. Banerjee and B. Chandrasekaran. (2004) "Perceptual and action routines in diagrammatic reasoning for entity-reidentification", Proc. 24th Army Science Conf., FL.

• B. Chandrasekaran, U. Kurup, B. Banerjee, J. R. Josephson and R. Winkler. (2004) "An architecture for problem solving with diagrams", Diagrams 2004 – 3rd Intl. Conf. on the Theory and Application of Diagrams, University of Cambridge, UK. Appears in Diagrammatic Representation and Inference, A. Blackwell, K. Marriott and A. Shimojima, Editors, Lecture Notes in Artificial Intelligence 2980, Berlin: Springer-Verlag, pp. 151-165. [Acceptance rate 34%]

• B. Chandrasekaran, J. R. Josephson, B. Banerjee, U. Kurup and R. Winkler. (2002) "Diagrammatic reasoning in support of situation understanding and planning", Proc. 23rd Army Science Conf., FL. Another version of this paper appeared in the Proc. of US Army Research Laboratory Collaborative Technology Symp. in April 2003, Washington DC, USA.

• B. Coifman and B. Banerjee. (2002) "Vehicle reidentification and travel time measurement on freeways using single loop detectors – from freeflow through the onset of congestion", Proc. 7th Intl. Conf. on Applications of Advanced Technology in Transportation, pp. 40-47, Cambridge, MA.

• B. Banerjee, A. Konar and S. Mukhopadhyay. (2000) "A neuro-GA approach for the navigational planning of a mobile robot", Proc. Intl. Conf. on Communications, Computers and Devices, IIT Kharagpur, India, pp. 625-628.

• B. Banerjee and I. S. Misra. (2000) "A neuro-computing model for the design of patch antennas", Proc. Intl. Conf. on Communications, Computers and Devices, IIT Kharagpur, India, pp. 340-343. (An extended version of this paper was published as a journal article in 2003.)

Extended Abstracts

• A. Dutta*, B. Banerjee, S. Khan and S. Chauhan. (2021) "Using machine learning to identify the risk factors of pancreatic cancer from the PLCO dataset", AACR Artificial Intelligence, Diagnosis, and Imaging Conference, January 13-14.

• M. H. Kapourchali* and B. Banerjee. (2020) "Learning what to communicate between agents for monitoring smart homes", International Symposium on Artificial Intelligence and Brain Science, October 10-12, Tokyo, Japan.

• M. H. Kapourchali* and B. Banerjee. (2020) "Learning communication policies for knowledge transfer between agents", CogSci 2020: 42nd Annual Meeting of the Cognitive Science Society, July 29-August 1. 

• I. B. Ray, M. H. Kapourchali*, B. Banerjee and K. Sakauye.  (2020) "Utilizing artificial intelligence to develop EKG sequence that can predict depression and the likely increased mortality and morbidity in cardiovascular disease", Heart Rhythm Conference, May 6-9, San Diego, CA. [Selected to be presented in the Cardiac Electrophysiology Society’s Young Investigator Award Poster Competition on Wednesday, May 6, 2020, 11:50 am-1:00 pm.]

• M. H. Kapourchali* and B. Banerjee. (2018) "A tensor based missing samples recovery for human movement acquisition", 15th International Conference on Wearable and Implantable Body Sensor Networks, March 4-7, Las Vegas, NV. 

• M. H. Kapourchali* and B. Banerjee. (2018) "Tuning deep brain stimulation parameters: An adaptive and individualized approach", 15th International Conference on Wearable and Implantable Body Sensor Networks, March 4-7, Las Vegas, NV.

• S. Najnin* and B. Banerjee. (2016) "Emergence of vocal developmental sequences in speech acquisition using a unified model of perception, action and learning", 15th Neural Computation and Psychology Workshop, August 8-9, Philadelphia, PA.

• M. H. Kapourchali* and B. Banerjee. (2016) "Analysis of clustering and sparse coding for feature learning from time-series", 15th Neural Computation and Psychology Workshop, August 8-9, Philadelphia, PA.

• L. L. Mendel, B. Banerjee, C. Patro*, S. Lee*, M. Pousson, S. Najnin*, J. K. Dutta* and M. H. Kapourchali*. (2016) "Tuning cochlear implants using patients’ speech production errors", XXXIII World Congress of Audiology, September 18-21, Vancouver, Canada.

• B. Banerjee, S. Najnin* and J. K. Dutta*. (2015) "Unraveling the objectives of computations in the peripheral auditory pathway", Conference on Implantable Auditory Prostheses (CIAP), July 12-17, Lake Tahoe, CA.

• S. Najnin*, B. Banerjee and L. L. Mendel. (2015) "Inferring hearing loss characteristics from statistically learned speech features", Conference on Implantable Auditory Prostheses (CIAP), July 12-17, Lake Tahoe, CA.

• B. Banerjee, L. L. Mendel, J. K. Dutta*, H. Shabani* and S. Najnin*. (2015) "Identifying hearing deficiencies from statistically learned speech features for personalized tuning of cochlear implants", Twenty-Ninth AAAI Conference on Artificial Intelligence Workshop (Artificial Intelligence Applied to Assistive Technologies and Smart Environments), January 25-29, Austin, TX.

• B. Banerjee, H. Shabani*, S. Najnin*, L. L. Mendel, C. Patro*, S. Lee* and M. P. King*. (2014) "Machine learning algorithms for tuning cochlear implants from speech production errors", Annual Convention of the American Academy of Audiology — AudiologyNOW!, March 26-29, Orlando, FL.

• B. Banerjee, A. Papanicolaou, S. Gao* and F. A. Tylavsky. (2013) "Audio features as marker of autism spectrum disorders in children", International Joint Conference on Neural Networks, August 4-9, 2013, Dallas, TX.

• B. Banerjee, A. Papanicolaou, S. Gao* and F. A. Tylavsky. (2013) "Can audio features serve as marker of autism spectrum disorders?", 17th International Conference on Cognitive and Neural Systems, June 4-7, 2013, Boston University, MA.

• B. Banerjee, J. Gu* and J. K. Dutta*. (2013) "Learning to discriminate with generative features", International Joint Conference on Neural Networks, August 4-9, 2013, Dallas, TX.

• B. Banerjee, J. K. Dutta* and J. Gu*. (2013) "Assigning uniqueness to generative features for discrimination", 17th International Conference on Cognitive and Neural Systems, June 4-7, 2013, Boston University, MA.

• J. K. Dutta* and B. Banerjee. (2013) "Learning complex cell receptive field properties by explaining simple cell responses over time", International Joint Conference on Neural Networks, August 4-9, 2013, Dallas, TX.

• J. K. Dutta* and B. Banerjee. (2013) "Learning complex cell receptive field properties using a generative model", 17th International Conference on Cognitive and Neural Systems, June 4-7, 2013, Boston University, MA.

• B. Banerjee. (2012) "Learning lateral connections among neurons from correlations of their surprises", Center for Visual Science's 28th Symposium: Computational Foundations of Perception and Action, June 1-3, 2012, University of Rochester, NY.

• J. K. Dutta*, J. Gu*, R. P. Kasani* and B. Banerjee. (2012) "A multilayered neural network model for verifying the common cortical algorithm hypothesis", Center for Visual Science's 28th Symposium: Computational Foundations of Perception and Action, June 1-3, 2012, University of Rochester, NY.

• B. Banerjee and B. Chandrasekaran. (2006) "Synthesizing visual and action routines using constraint programming", Diagrams 2006 - 4th Intl. Conf. on the Theory and Application of Diagrams, Stanford University, CA, June 28-30, 2006. Appears in Diagrammatic Representation and Inference, D. Barker-Plummer, R. Cox and N. Swoboda, Editors, Lecture Notes in Artificial Intelligence 4045, Springer Berlin, pp. 196-198.

• B. Chandrasekaran, U. Kurup and B. Banerjee. (2004) "Representational and inferential requirements for diagrammatic reasoning in the entity-reidentification task", Proc. 24th Army Science Conf., FL.

• B. Banerjee and B. Chandrasekaran. (2004) "Constructing diagrams representing group motions", Diagrams 2004 - 3rd Intl. Conf. on the Theory and Application of Diagrams, University of Cambridge, UK. Appears in Diagrammatic Representation and Inference, A. Blackwell, K. Marriott and A. Shimojima, Editors, Lecture Notes in Artificial Intelligence 2980, Berlin: Springer-Verlag, pp. 376-378.

Thesis/Dissertation/Technical Report

• B. Banerjee. (2007) "Spatial problem solving for diagrammatic reasoning", Ph.D. dissertation, Dept. of Computer Science & Engineering, The Ohio State University, Columbus.

• B. Banerjee, B. Chandrasekaran, J. R. Josephson and R. Winkler. (2003) "Constructing diagrams to support situation understanding and planning: Part 1: Diagramming group motions", Technical Report OSU-CISRC-5/03-TR29, Dept. of Computer Science & Engineering, The Ohio State University, Columbus.

• B. Banerjee. (2002) "Generating diagrams of group motions from locations and movements of individuals", M.S. thesis, Dept. of Electrical Engineering, The Ohio State University, Columbus.

• B. Banerjee and P. Mukhopadhyay. (2000) "Recognition of partially occluded and/or distorted shapes in a cluttered scene", B.E. thesis, Dept. of Electronics & Telecommunication Engineering, Jadavpur University, India. (An extended version of this thesis was published as a journal article in 2004.)