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2020 – today
- 2024
[c31]Aswathnarayan Radhakrishnan, Jim Davis, Zachary Rabin, Benjamin Lewis, Matthew Scherreik, Roman Ilin:
Design Choices for Enhancing Noisy Student Self-Training. WACV 2024: 1915-1924- 2023
- [i4]Aswathnarayan Radhakrishnan, Jim Davis, Zachary Rabin, Benjamin Lewis, Matthew Scherreik, Roman Ilin:
Enhancing Self-Training Methods. CoRR abs/2301.07294 (2023) - 2021
- [j7]Roman Ilin
:
Detection of rare events with uncertain outcomes. Int. J. Approx. Reason. 131: 252-267 (2021) - [c30]Nicholas Kashani Motlagh, Aswathnarayan Radhakrishnan, Jim Davis, Roman Ilin:
A Framework for Semi-automatic Collection of Temporal Satellite Imagery for Analysis of Dynamic Regions. ICCVW 2021: 704-712 - [i3]Tong Liang, Jim Davis, Roman Ilin:
Bottom-up Hierarchical Classification Using Confusion-based Logit Compression. CoRR abs/2110.01756 (2021) - 2020
- [c29]Galina L. Rogova, Roman Ilin:
Decision Making with "Gray Swan" events. CogSIMA 2020: 12-19 - [c28]Jingyang Lu, Chenggang Yu, Erik Blasch, Roman Ilin, Hua-mei Chen, Dan Shen, Nichole Sullivan, Genshe Chen, Robert Kozma:
Deep Learning Based Domain Adaptation with Data Fusion for Aerial Image Data Analysis. ICPR Workshops (8) 2020: 118-133 - [c27]Jim Davis, Tong Liang, James Enouen, Roman Ilin:
Hierarchical Classification with Confidence using Generalized Logits. ICPR 2020: 1874-1881
2010 – 2019
- 2019
- [c26]Galina L. Rogova, Roman Ilin:
Reasoning and Decision Making under Uncertainty and Risk for Situation Management. CogSIMA 2019: 34-42 - [c25]Galina L. Rogova, Roman Ilin:
Multi-Agent System for Threat Assessment and Action Selection under Uncertainty and Ambiguity. FUSION 2019: 1-8 - [c24]Jim Davis, Tong Liang, James Enouen, Roman Ilin:
Hierarchical Semantic Labeling with Adaptive Confidence. ISVC (2) 2019: 169-183 - [c23]Aswathnarayan Radhakrishnan, James Cunningham, Jim Davis, Roman Ilin:
A Framework for Collecting and Classifying Objects in Satellite Imagery. ISVC (2) 2019: 295-306 - 2018
- [c22]Galina L. Rogova, Roman Ilin:
Action Selection Under Uncertainty and Risk Involving High Consequence Rare Events. CogSIMA 2018: 8-14 - [c21]Roman Ilin, Galina L. Rogova:
Multi-Model Threat Assessment Involving Low Probability High Consequence Events. FUSION 2018: 1836-1843 - [c20]Robert Kozma, Roman Ilin, Hava T. Siegelmann:
Evolution of Abstraction Across Layers in Deep Learning Neural Networks. INNS Conference on Big Data 2018: 203-213 - [i2]James W. Davis, Christopher Menart, Muhammad Akbar, Roman Ilin:
A Classification Refinement Strategy for Semantic Segmentation. CoRR abs/1801.07674 (2018) - 2017
- [c19]Roman Ilin, Galina L. Rogova:
Decision-making involving low probability high consequence events under risk and uncertainty. CogSIMA 2017: 1-5 - [c18]Roman Ilin, Thomas Watson, Robert Kozma:
Abstraction hierarchy in deep learning neural networks. IJCNN 2017: 768-774 - 2016
- [c17]Roman Ilin, Rauf Izmailov, Yuri Goncharov, Simon Streltsov:
Fusion of privileged features for efficient classifier training. FUSION 2016: 1382-1389 - [c16]Roman Ilin:
Classification with Concept Lattice and Choquet integral. FUSION 2016: 1554-1561 - 2015
- [c15]Roman Ilin, Erik Blasch:
Information fusion with belief functions: A comparison of proportional conflict redistribution PCR5 and PCR6 rules for networked sensors. FUSION 2015: 2084-2091 - [c14]Roman Ilin, Jun Zhang:
Information fusion with topological event spaces. FUSION 2015: 2092-2099 - 2014
- [j6]Roman Ilin, Simon Streltsov, Rauf Izmailov:
Learning with Privileged Information for Improved Target Classification. Int. J. Monit. Surveillance Technol. Res. 2(3): 50-66 (2014) - [c13]Jayanta K. Dutta, Bonny Banerjee, Roman Ilin, Robert Kozma:
Abnormal event detection in EEG imaging - Comparing predictive and model-based approaches. CIBCI 2014: 10-15 - [c12]Roman Ilin, Jun Zhang:
Information fusion with uncertainty modeled on topological event spaces. FOCI 2014: 1-8 - [c11]Mark H. Myers, Robert Kozma, Jeffery Jonathan Davis, Roman Ilin:
Phase cone detection optimization in EEG data. IJCNN 2014: 2504-2511 - 2013
- [c10]Roman Ilin, Robert Kozma:
Detection of spatiotemporal phase patterns in ECoG using adaptive mixture models. IJCNN 2013: 1-7 - 2012
- [j5]Roman Ilin:
Unsupervised Learning of Categorical Data With Competing Models. IEEE Trans. Neural Networks Learn. Syst. 23(11): 1726-1737 (2012) - [c9]Roman Ilin, Robert Kozma:
Cognitively motivated learning of categorical data with Modeling Fields Theory. IJCNN 2012: 1-8 - 2011
- [c8]Leonid I. Perlovsky, Roman Ilin:
Neurally and Mathematically Motivated Architecture for Language and Cognition. BICA 2011: 288 - [c7]Roman Ilin, Leonid I. Perlovsky:
Dynamic Logic learning in cognitive-based situation models. CogSIMA 2011: 32-39 - 2010
- [j4]Roman Ilin, Leonid I. Perlovsky:
Cognitively Inspired Neural Network for Recognition of Situations. Int. J. Nat. Comput. Res. 1(1): 36-55 (2010) - [c6]Leonid I. Perlovsky, Roman Ilin:
Grounded symbols in the brain. IJCNN 2010: 1-10 - [c5]Leonid I. Perlovsky, Roman Ilin:
The knowledge instinct of autonomous adaptation. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j3]José Fernando Fontanari, Vadim Tikhanoff, Angelo Cangelosi, Roman Ilin, Leonid I. Perlovsky:
Cross-situational learning of object-word mapping using Neural Modeling Fields. Neural Networks 22(5-6): 579-585 (2009) - [c4]Roman Ilin, Robert Kozma:
Sensor integration in KIV brain model for decision making. IJCNN 2009: 1328-1334 - 2008
- [j2]Robert Kozma, Terry Huntsberger, Hrand Aghazarian, Edward W. Tunstel, Roman Ilin, Walter J. Freeman:
Intentional Control for Planetary Rover SRR. Adv. Robotics 22(12): 1309-1327 (2008) - [j1]Roman Ilin, Robert Kozma, Paul J. Werbos:
Beyond Feedforward Models Trained by Backpropagation: A Practical Training Tool for a More Efficient Universal Approximator. IEEE Trans. Neural Networks 19(6): 929-937 (2008) - 2007
- [c3]Roman Ilin, Robert Kozma:
Control of multi-stable chaotic neural networks using input constraints. IJCNN 2007: 2194-2199 - [i1]Roman Ilin, Robert Kozma, Paul J. Werbos:
Beyond Feedforward Models Trained by Backpropagation: a Practical Training Tool for a More Efficient Universal Approximator. CoRR abs/0710.4182 (2007) - 2006
- [c2]Roman Ilin, Robert Kozma, Paul J. Werbos:
Cellular SRN Trained by Extended Kalman Filter Shows Promise for ADP. IJCNN 2006: 506-510 - 2005
- [c1]Igor Beliaev, Roman Ilin, Robert Kozma:
Nonlinear Neurodynamics Tool for System Analysis and Application for Time Series Prediction. SMC 2005: 1011-1016
Coauthor Index
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