New SNR estimate for the Wiener filter to image restoration. - Shan Suthaharan (J. Electronic Imaging, 1994)

Adaptive-Neighbourhood Image Filtering for Mpeg-1 Coded Images. - Shan Suthaharan; Hong Ren Wu (ISSPA, 1996)

Generation of signal-uncorrelated noise for control experiments in image restoration. - Shan Suthaharan; S. Ray (Pattern Recognit. Lett., 1996)

SNR Optimization Using Genetic Algorithm. - Shan Suthaharan; Zhongwei Zhang (ICIP (1), 1997)

Joint Source/Channel Coding to Maximize Perceptual Video Quality on Packet Networks. - Seong-Whan Kim; Shan Suthaharan; Geun-Ho Lee; Heung-Kyu Lee; K. R. Rao (Real Time Imaging, 1999)

Neuro-Fuzzy Modeling and Prediction of VBR MPEG Video Sources. - Bin Qiu; Shan Suthaharan; Hong Ren Wu (Real Time Imaging, 1999)

Guest Editorial: Special Issue on Real-Time Digital Video over Multimedia Networks. - Shan Suthaharan; Sivapragasam Sathananthan; Carl Pantsios Markhauser; Ling Guan (Real Time Imaging, 1999)

Perceptually most significant edge detection algorithm for object-based coding. - Shan Suthaharan; Hong Ren Wu; K. R. Rao (VCIP, 2000)

Image and edge detail detection algorithm for object-based coding. - Shan Suthaharan (Pattern Recognit. Lett., 2000)

Perceptually tuned robust watermarking scheme for digital images. - Shan Suthaharan; Seong-Whan Kim; Heung-Kyu Lee; Sivapragasam Sathananthan (Pattern Recognit. Lett., 2000)

MPEG-compliant joint source/channel coding using discrete cosine transform and substream scheduling for visual communication over packet networks. - Seong-Whan Kim; Shan Suthaharan; Heung-Kyu Lee; K. R. Rao 001 (J. Electronic Imaging, 2001)

Fuzzy Logic Strategy of Prognosticating TCP's Timeout ad Retransmission. - Zhongwei Zhang; Zhi Li 006; Shan Suthaharan (FSKD, 2002)

A perceptually significant block-edge impairment metric for digital video coding. - Shan Suthaharan (ICASSP (3), 2003)

Markov Model Based Congestion Control for TCP. - Shan Suthaharan (Annual Simulation Symposium, 2004)

Perceptually Tuned Packet Scheduler for Video Streaming for DAB Based Access GRID. - Seong-Whan Kim; Shan Suthaharan (GCC, 2004)

An Entropy Masking Model for Multimedia Content Watermarking. - Seong-Whan Kim; Shan Suthaharan (HICSS, 2004)

Fragile image watermarking using a gradient image for improved localization and security. - Shan Suthaharan (Pattern Recognit. Lett., 2004)

Low bit-rate multimedia communication. - Shan Suthaharan; Mrinal K. Mandal 001 (Real Time Imaging, 2004)

Fuzzy Logic Strategy of Prognosticating TCP's Timeout and Retransmission. - Zhongwei Zhang; Zhi Li 006; Shan Suthaharan (Computational Intelligence for Modelling and Prediction, 2005)

Reduction of queue oscillation in the next generation Internet routers. - Shan Suthaharan (Comput. Commun., 2007)

A no-reference Spatial Aliasing Measure for digital image resizing. - Amy R. Reibman; Shan Suthaharan (ICIP, 2008)

Chaos-based image encryption scheme using Galois field for fast and secure transmission. - Shan Suthaharan (Real-Time Image Processing, 2008)

Enhanced Accuracy Moment Invariants for Biometric Recognition and Cryptosystems. - Shan Suthaharan (ICIAR, 2009)

Energy Efficient DNA-Based Scheduling Scheme for Wireless Sensor Networks. - Shan Suthaharan; Abhinav Chawade; Rittwik Jana; Jing Deng 001 (WASA, 2009)

No-reference visually significant blocking artifact metric for natural scene images. - Shan Suthaharan (Signal Process., 2009)

Sensor data boundary estimation for anomaly detection in wireless sensor networks. - Shan Suthaharan; Christopher Leckie; Masud Moshtaghi; Shanika Karunasekera; Sutharshan Rajasegarar (MASS, 2010)

Logistic Map-Based Fragile Watermarking for Pixel Level Tamper Detection and Resistance. - Shan Suthaharan (EURASIP J. Inf. Secur., 2010)

A unit-circle classification algorithm to characterize back attack and normal traffic for intrusion detection. - Shan Suthaharan (ISI, 2012)

Lame' curve-based signature discovery learning technique for network traffic classification. - Shan Suthaharan; Laxmi Sunkara; Sweta Keshapagu (ISI, 2013)

A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion. - Shan Suthaharan (MLDM, 2013)

Modeling of class imbalance using an empirical approach with spambase dataset and random forest classification. - Kiranmayi Kotipalli; Shan Suthaharan (RIIT, 2014)

FLaSKU - a classroom experience with teaching computer networking: is it useful to others in the field? - Shan Suthaharan (SIGITE, 2014)

Big data classification: problems and challenges in network intrusion prediction with machine learning. - Shan Suthaharan (SIGMETRICS Perform. Evaluation Rev., 2014)

Security problems and challenges in a machine learning-based hybrid big data processing network systems. - Jeff Whitworth; Shan Suthaharan (SIGMETRICS Perform. Evaluation Rev., 2014)

A correlation-based subspace analysis for data confidentiality and classification as utility in CPS. - Shan Suthaharan (CNS, 2016)

Pairing of most relevant variables and bootstrap samples with ridge regression for data sharing. - Shan Suthaharan; Weining Shen (CNS, 2016)

A fatal point concept and a low-sensitivity quantitative measure for traffic safety analytics. - Shan Suthaharan (CoRR, 2017)

Characterization of differentially private logistic regression. - Shan Suthaharan (ACM Southeast Regional Conference, 2018)

A software engineering schema for data intensive applications. - Shan Suthaharan (ACM Southeast Regional Conference, 2018)

Feature Extraction Using Apparent Power and Real Power for Smart Home Data Classification. - Vishali Vadakattu; Shan Suthaharan (ICMLA, 2018)

What we learn from learning - Understanding capabilities and limitations of machine learning in botnet attacks. - David Santana; Shan Suthaharan; Somya D. Mohanty (CoRR, 2018)

Privacy-Preserving Predictive Model Using Factor Analysis for Neuroscience Applications. - Suprateek Kundu; Shan Suthaharan (BigDataSecurity/HPSC/IDS, 2019)

Towards Encapsulated Cyber Security Labs: A Container Based Approach. - Selvarajah Mohanarajah; Gregorry Ross; Shan Suthaharan (SIGCSE, 2019)

Elliptical modeling and pattern analysis for perturbation models and classification. - Shan Suthaharan; Weining Shen (Int. J. Data Sci. Anal., 2019)

An enhanced support vector machine model for urban expansion prediction. - Firoozeh Karimi; Selima Sultana; Ali Shirzadi Babakan; Shan Suthaharan (Comput. Environ. Urban Syst., 2019)

Big data analytics: Machine learning and Bayesian learning perspectives - What is done? What is not? - Shan Suthaharan (WIREs Data Mining Knowl. Discov., 2019)

Pixel-Level Feature Space Modeling and Brain Tumor Detection Using Machine Learning. - Ritu Joshi; Shan Suthaharan (ICMLA, 2020)

A low-sensitivity quantitative measure for traffic safety data analytics. - Shan Suthaharan (Int. J. Data Sci. Anal., 2020)

Laplacian feature detection and feature alignment for multimodal ophthalmic image registration using phase correlation and Hessian affine feature space. - Shan Suthaharan; Ethan A. Rossi; Valerie Snyder; Jay Chhablani; Raphael Lejoyeux; José-Alain Sahel; Kunal K. Dansingani (Signal Process., 2020)

NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniques. - Gunjan Chhablani; Abheesht Sharma; Harshit Pandey; Yash Bhartia; Shan Suthaharan (SemEval@ACL/IJCNLP, 2021)

Facial Emotion Characterization and Detection using Fourier Transform and Machine Learning. - Aishwarya Gouru; Shan Suthaharan (CoRR, 2021)

Urban expansion modeling using an enhanced decision tree algorithm. - Firoozeh Karimi; Selima Sultana; Ali Shirzadi Babakan; Shan Suthaharan (GeoInformatica, 2021)

Robust Retinal Layer Segmentation Using OCT B-Scans: A Novel Approach Based on Pix2Pix Generative Adversarial Network. - Adarsh Gadari; Sandeep Chandra Bollepalli; Mohammed Nasar Ibrahim; José-Alain Sahel; Jay Chhablani; Shan Suthaharan; Kiran Kumar Vupparaboina (BCB, 2023)

Fall Detection using Machine Learning Techniques and Frequency-Driven Riemannian Manifolds. - Shan Suthaharan (ICMLA, 2023)

Microsaccade Segmentation using Directional Variance Analysis and Artificial Neural Networks. - Shan Suthaharan; Lee Daniel M. W.; Min Zhang; Ethan A. Rossi (IRI, 2023)

Harnessing the Feature Vectors of VGG-16 for Birds Detection under Geometric Distortions and Brightness. - Shan Suthaharan (TransAI, 2023)

LDEB - Label Digitization with Emotion Binarization and Machine Learning for Emotion Recognition in Conversational Dialogues. - Amitabha Dey; Shan Suthaharan (CoRR, 2023)

Modeling and simulation of a Tamil language encoder for advanced encryption technologies. - Shan Suthaharan (Patterns, 2023)

A Nature-Inspired Colony of Artificial Intelligence System with Fast, Detailed, and Organized Learner Agents for Enhancing Diversity and Quality. - Shan Suthaharan (AAAI Spring Symposia, 2025)