Thomas P. Trappenberg

Publication Activity (10 Years)

Years Active: 1994-2019
Publications (10 Years): 15

Top Topics

Lesion Segmentation

Dermoscopy Images

Top Venues

Canadian Conference on AI

Neural Networks

Publications

Abder-Rahman Ali, Jingpeng Li, Thomas P. Trappenberg
Supervised Versus Unsupervised Deep Learning Based Methods for Skin Lesion Segmentation in Dermoscopy Images. Canadian Conference on AI (2019)
Abder-Rahman Ali, Jingpeng Li, Sally Jane O'Shea, Guang Yang, Thomas P. Trappenberg, Xujiong Ye
A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images. IJCNN (2019)
André G. C. Pacheco, Abder-Rahman Ali, Thomas P. Trappenberg
Skin cancer detection based on deep learning and entropy to detect outlier samples. CoRR (2019)
Peter Q. Lee, Alessandro Guida, Steve Patterson, Thomas P. Trappenberg, Chris V. Bowen, Steven D. Beyea, Jennifer Merrimen, Cheng Wang, Sharon E. Clarke
Model-free prostate cancer segmentation from dynamic contrast-enhanced MRI with recurrent convolutional networks: A feasibility study. Comput. Medical Imaging Graph. 75 (2019)
Pitoyo Hartono, Thomas P. Trappenberg
Topographic representation adds robustness to supervised learning. J. Intell. Fuzzy Syst. 36 (4) (2019)
Farzaneh Sheikhnezhad Fard, Thomas P. Trappenberg
A Novel Model for Arbitration Between Planning and Habitual Control Systems. Frontiers Neurorobotics 13 (2019)
Junliang Luo, Sageev Oore, Paul Hollensen, Alan Fine, Thomas P. Trappenberg
Self-training for Cell Segmentation and Counting. Canadian Conference on AI (2019)
Yoshimasa Kubo, Thomas P. Trappenberg
Mitigating Overfitting Using Regularization to Defend Networks Against Adversarial Examples. Canadian Conference on AI (2019)
Francesco Usai, Thomas P. Trappenberg
Using a Deep CNN for Automatic Classification of Sleep Spindles: A Preliminary Study. Canadian Conference on AI (2019)
Michael Traynor, Thomas P. Trappenberg
Words Are Not Temporal Sequences of Characters. IJCNN (2018)
Farzaneh Sheikhnezhad Fard, Thomas P. Trappenberg
Mixing Habits and Planning for Multi-Step Target Reaching Using Arbitrated Predictive Actor-Critic. IJCNN (2018)
Farzaneh Sheikhnezhad Fard, Paul Hollensen, Stuart McIlroy, Thomas P. Trappenberg
Impact of biased mislabeling on learning with deep networks. IJCNN (2017)
Farzaneh Sheikhnezhad Fard, Thomas P. Trappenberg
A Novel Model for Arbitration between Planning and Habitual Control Systems. CoRR (2017)
Stuart McIlroy, Yoshimasa Kubo, Thomas P. Trappenberg, James Toguri, Christian Lehmann
In vivo classification of inflammation in blood vessels with convolutional neural networks. IJCNN (2017)
Chun Kwang Tan, Paul G. Plöger, Thomas P. Trappenberg
A Neural Field Approach to Obstacle Avoidance. KI (2016)
Pitoyo Hartono, Paul Hollensen, Thomas P. Trappenberg
Classifier with Hierarchical Topographical Maps as Internal Representation. ICLR (Workshop) (2015)
Hossein Parvar, Lauren D. Sculthorpe-Petley, Jason Satel, Rober Boshra, Ryan C. N. D'Arcy, Thomas P. Trappenberg
Detection of event-related potentials in individual subjects using support vector machines. Brain Informatics 2 (1) (2015)
Farzaneh Sheikhnezhad Fard, Paul Hollensen, Dietmar Heinke, Thomas P. Trappenberg
Modeling human target reaching with an adaptive observer implemented with dynamic neural fields. Neural Networks 72 (2015)
Patrick C. Connor, Paul Hollensen, Olav E. Krigolson, Thomas P. Trappenberg
A biological mechanism for Bayesian feature selection: Weight decay and raising the LASSO. Neural Networks 67 (2015)
Pitoyo Hartono, Paul Hollensen, Thomas P. Trappenberg
Learning-Regulated Context Relevant Topographical Map. IEEE Trans. Neural Networks Learn. Syst. 26 (10) (2015)
Jason Satel, Farzaneh Sheikhnezhad Fard, Zhiguo Wang, Thomas P. Trappenberg
Simulating oculomotor inhibition of return with a two-dimensional dynamic neural field model of the superior colliculus. Aust. J. Intell. Inf. Process. Syst. 14 (1) (2014)
Patrick C. Connor, Thomas P. Trappenberg
An Architecture for Distinguishing between Predictors and Inhibitors in Reinforcement Learning. ICLR (Workshop Poster) (2014)
Pitoyo Hartono, Paul Hollensen, Thomas P. Trappenberg
Visualizing Hierarchical Representation in a Multilayered Restricted RBF Network. ICANN (2014)
Pitoyo Hartono, Thomas P. Trappenberg
Classificability-regulated self-organizing map using restricted RBF. IJCNN (2013)
Patrick C. Connor, Thomas P. Trappenberg
Biologically plausible feature selection through relative correlation. IJCNN (2013)
Thomas P. Trappenberg
Bubbles in the robot. IJCNN (2013)
Warren A. Connors, Thomas P. Trappenberg
Improved Path Integration Using a Modified Weight Combination Method. Cogn. Comput. 5 (3) (2013)
Robert A. Marino, Thomas P. Trappenberg, Michael Dorris, Douglas P. Munoz
Spatial Interactions in the Superior Colliculus Predict Saccade Behavior in a Neural Field Model. J. Cogn. Neurosci. 24 (2) (2012)
Pitoyo Hartono, Thomas P. Trappenberg
Internal representation of sensory information for training autonomous robot. SCIS&ISIS (2012)
Misha Denil, Thomas P. Trappenberg
A Characterization of the Combined Effects of Overlap and Imbalance on the SVM Classifier CoRR (2011)
Patrick C. Connor, Thomas P. Trappenberg
Characterizing a Brain-Based Value-Function Approximator. Canadian Conference on AI (2011)
Pitoyo Hartono, Thomas P. Trappenberg
Internal topographical structure in training autonomous robot. SMC (2011)
Paul Hollensen, Warren A. Connors, Thomas P. Trappenberg
Comparison of Learned versus Engineered Features for Classification of Mine Like Objects from Raw Sonar Images. Canadian Conference on AI (2011)
Warren A. Connors, Patrick C. Connor, Thomas P. Trappenberg
Detection of Mine-Like Objects Using Restricted Boltzmann Machines. Canadian Conference on AI (2010)
Misha Denil, Thomas P. Trappenberg
Overlap versus Imbalance. Canadian Conference on AI (2010)
Thomas P. Trappenberg, Aya Saito, Pitoyo Hartono
Selective attention improves self-organization of cortical maps with multiple inputs. IJCNN (2010)
Thomas P. Trappenberg, Pitoyo Hartono, Douglas Rasmusson
Top-Down Control of Learning in Biological Self-Organizing Maps. WSOM (2009)
Pitoyo Hartono, Thomas P. Trappenberg
Learning Intialized by Topologically Correct Representation. SMC (2009)
Joshua P. Salmon, Thomas P. Trappenberg
Modeling the integration of expectations in visual search with centre-surround neural fields. Neural Networks 21 (10) (2008)
Dominic I. Standage, Thomas P. Trappenberg
The Trouble with Weight-Dependent STDP. IJCNN (2007)
Dominic I. Standage, Sajiya Jalil, Thomas P. Trappenberg
Computational consequences of experimentally derived spike-time and weight dependent plasticity rules. Biol. Cybern. 96 (6) (2007)
Michael Lawrence, Thomas P. Trappenberg, Alan Fine
Rapid learning and robust recall of long sequences in modular associator networks. Neurocomputing 69 (7-9) (2006)
Thomas P. Trappenberg, Jie Ouyang, Andrew D. Back
Input Variable Selection: Mutual Information and Linear Mixing Measures. IEEE Trans. Knowl. Data Eng. 18 (1) (2006)
Matthew Boardman, Thomas P. Trappenberg
A Heuristic for Free Parameter Optimization with Support Vector Machines. IJCNN (2006)
Thomas P. Trappenberg
Coverage-performance estimation for classification with ambiguous data. ESANN (2005)
Dominic I. Standage, Thomas P. Trappenberg, Raymond M. Klein
Modelling divided visual attention with a winner-take-all network. Neural Networks 18 (5-6) (2005)
Michael Lawrence, Thomas P. Trappenberg, Alan Fine
A multi-modular associator network for simple temporal sequence learning and generation. ESANN (2005)
Thomas P. Trappenberg, Dominic I. Standage
Multi-packet regions in stabilized continuous attractor networks. Neurocomputing (2005)
Simon M. Stringer, Edmund T. Rolls, Thomas P. Trappenberg
Self-organising continuous attractor networks with multiple activity packets, and the representation of space. Neural Networks 17 (1) (2004)
Simon M. Stringer, Edmund T. Rolls, Thomas P. Trappenberg, Ivan E. Tavares de Araújo
Self-organizing continuous attractor networks and motor function. Neural Networks 16 (2) (2003)
Thomas P. Trappenberg, Edmund T. Rolls, Simon M. Stringer
Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes. NIPS (2001)
Andrew D. Back, Thomas P. Trappenberg
Selecting inputs for modeling using normalized higher order statistics and independent component analysis. IEEE Trans. Neural Networks 12 (3) (2001)
Thomas P. Trappenberg, Andrew D. Back
A Classification Scheme for Applications with Ambiguous Data. IJCNN (6) (2000)
Andrew D. Back, Thomas P. Trappenberg
Input variable selection using independent component analysis. IJCNN (1999)
Lars Kindermann, Thomas P. Trappenberg
Modeling time-varying processes by unfolding the time domain. IJCNN (1999)
Thomas P. Trappenberg
Dynamic Cooperation and Competition in a Network of Spiking Neurons. ICONIP (1998)
Thomas P. Trappenberg, S. Simpson, Raymond M. Klein, P. McMullen, Douglas P. Munoz, Michael Dorris
Neural field model of oculomotor preparation and disengagement. ICNN (1997)
K. J. M. Moriarty, Sergiu Sanielevici, Thomas P. Trappenberg
High Speed Monte Carlo Simulations on Vector Parallel Computers. Parallel Algorithms Appl. 3 (3-4) (1994)