SAIM: A Model of Visual Attention and Neglect. - Dietmar Heinke; Glyn W. Humphreys (ICANN, 1997)

Selection for Object Identification: Modelling Emergent Attentional Processes in Normality and Pathology. - Glyn W. Humphreys; Dietmar Heinke (NCPW, 1997)

Comparing neural networks: a benchmark on growing neural gas, growing cell structures, and fuzzy ARTMAP. - Dietmar Heinke; Fred H. Hamker (IEEE Trans. Neural Networks, 1998)

Selbstorganisation einer zeitlichen Objektpräsentation. - Dietmar Heinke (Logos-Verlag, 1998)

A computational neuroscience account of visual neglect. - Dietmar Heinke; Gustavo Deco; Josef Zihl; Glyn W. Humphreys (Neurocomputing, 2002)

Modelling visual search experiments: the selective attention for identification model (SAIM). - Dietmar Heinke; Glyn W. Humphreys; Giovanni di Virgilio (Neurocomputing, 2002)

Modeling Grouping Through Interactions Between Top-Down and Bottom-Up Processes: The Grouping and Selective Attention for Identification Model (G-SAIM). - Dietmar Heinke; Yaoru Sun; Glyn W. Humphreys (WAPCV, 2004)

Contextual Learning in the Selective Attention for Identification model (CL-SAIM): Modeling contextual cueing in visual search tasks. - Andreas Backhaus; Dietmar Heinke; Glyn W. Humphreys (CVPR Workshops, 2005)

Selective Attention for Identification Model: Simulating visual neglect. - Dietmar Heinke; Glyn W. Humphreys (Comput. Vis. Image Underst., 2005)

The Selective Attention for Identification Model (SAIM): Simulating Visual Search in Natural Colour Images. - Dietmar Heinke; Andreas Backhaus; Yaoru Sun; Glyn W. Humphreys (WAPCV, 2007)

The Spiking Search over Time and Space Model (sSoTS): Simulating Dual Task Experiments and the Temporal Dynamics of Preview Search. - Eirini Mavritsaki; Dietmar Heinke; Glyn W. Humphreys; Gustavo Deco (WAPCV, 2007)

Suppressive effects in visual search: A neurocomputational analysis of preview search. - Eirini Mavritsaki; Dietmar Heinke; Glyn W. Humphreys; Gustavo Deco (Neurocomputing, 2007)

Where Do We Grasp Objects? - An Experimental Verification of the Selective Attention for Action Model (SAAM). - Christoph Böhme; Dietmar Heinke (WAPCV, 2008)

Modelling Visual Search with the Selective Attention for Identification Model (VS-SAIM): A Novel Explanation for Visual Search Asymmetries. - Dietmar Heinke; Andreas Backhaus (Cogn. Comput., 2011)

An Agent-Based Simulation of Destigmatization (DSIM): Introducing a Contact Theory and Self-Fulfilling Prophecy Approach. - Dietmar Heinke; Gregory Carslaw; Julie Christian (J. Artif. Soc. Soc. Simul., 2013)

Modeling human target reaching with an adaptive observer implemented with dynamic neural fields. - Farzaneh Sheikhnezhad Fard; Paul Hollensen; Dietmar Heinke; Thomas Trappenberg (Neural Networks, 2015)

Choice reaching with a LEGO arm robot (CoRLEGO): The motor system guides visual attention to movement-relevant information. - Soeren Strauss; Philip J. W. Woodgate; Saber A. Sami; Dietmar Heinke (Neural Networks, 2015)

An Agent-Based Model for False Belief Tasks: Belief Representation Systematic Approach (BRSA). - Zahrieh Yousefi; Dietmar Heinke; Ian Apperly; Peer-Olaf Siebers (SBP-BRiMS, 2018)

Human Interaction and Improving Knowledge through Collaborative Tour Guide Robots. - Anna-Maria Velentza; Dietmar Heinke; Jeremy L. Wyatt (RO-MAN, 2019)

Museum robot guides or conventional audio guides? An experimental study. - Anna-Maria Velentza; Dietmar Heinke; Jeremy L. Wyatt (Adv. Robotics, 2020)

Continuous action with a neurobiologically inspired computational approach reveals the dynamics of selection history. - Mukesh Makwana; Fan Zhang; Dietmar Heinke; Joo-Hyun Song (PLoS Comput. Biol., 2023)

CoCoG: Controllable Visual Stimuli Generation Based on Human Concept Representations. - Chen Wei 006; Jiachen Zou; Dietmar Heinke; Quanying Liu (IJCAI, 2024)

CoCoG-2: Controllable generation of visual stimuli for understanding human concept representation. - Chen Wei 006; Jiachen Zou; Dietmar Heinke; Quanying Liu (CoRR, 2024)

Support for the Time-Varying Drift Rate Model of Perceptual Discrimination in Dynamic and Static Noise Using Bayesian Model-Fitting Methodology. - Jordan Deakin; Andrew Schofield; Dietmar Heinke (Entropy, 2024)

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability. - Chen Wei 006; Chi Zhang; Jiachen Zou; Haotian Deng; Dietmar Heinke; Quanying Liu (CoRR, 2025)