Justus Piater mostly deals with Artificial intelligence, Computer vision, Robot, Object and Pattern recognition. He has included themes like Machine learning, Affordance and GRASP in his Artificial intelligence study. His research in Computer vision intersects with topics in Activity recognition, Retina and Sensory cue.
His work carried out in the field of Robot brings together such families of science as Visual perception, Salient, Unsupervised learning and Human–computer interaction. His Object study combines topics in areas such as Symbolic data analysis, Planning Domain Definition Language and Top-down and bottom-up design. Justus Piater combines subjects such as Overfitting, Visual space and Robustness with his study of Pattern recognition.
His primary areas of study are Artificial intelligence, Computer vision, Machine learning, Robot and Object. His Artificial intelligence research incorporates elements of Affordance, GRASP and Pattern recognition. The concepts of his Pattern recognition study are interwoven with issues in Contextual image classification, Cognitive neuroscience of visual object recognition and Feature.
His work in the fields of Video tracking, Tracking and Particle filter overlaps with other areas such as Belief propagation. His Robot study integrates concerns from other disciplines, such as Context and Human–computer interaction. Many of his studies on Object involve topics that are commonly interrelated, such as Representation.
Justus Piater focuses on Artificial intelligence, Robot, Machine learning, Object and Human–computer interaction. His biological study spans a wide range of topics, including Context, Affordance and Computer vision. Justus Piater has researched Robot in several fields, including Training set and Robustness.
The Machine learning study combines topics in areas such as State, State prediction and Perception. His study in Object is interdisciplinary in nature, drawing from both Motion, GRASP and Mobile robot. The various areas that Justus Piater examines in his Human–computer interaction study include Assistive robot and Robot software.
The scientist’s investigation covers issues in Artificial intelligence, Robot, Computer vision, Robotics and Human–computer interaction. His Artificial intelligence study incorporates themes from Context, Machine learning and Affordance. His Robot research includes elements of Object, Training set and Generalization.
His work on Pose as part of general Computer vision research is frequently linked to Wrist, Force sensor and Handover, bridging the gap between disciplines. His Robotics research incorporates themes from Cognitive science and Taxonomy. His Human–computer interaction research is multidisciplinary, relying on both Representation and Mobile robot.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Random subwindows for robust image classification
R. Maree;P. Geurts;J. Piater;L. Wehenkel.
computer vision and pattern recognition (2005)
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
N. Kruger;P. Janssen;S. Kalkan;M. Lappe.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)
Object-action complexes: Grounded abstractions of sensory-motor processes
Norbert Krüger;Christopher W. Geib;Justus H. Piater;Ronald P. A. Petrick.
Robotics and Autonomous Systems (2011)
Learning Grasp Affordance Densities
Renaud Detry;Dirk Kraft;Oliver Kroemer;Leon Bodenhagen.
Paladyn: Journal of Behavioral Robotics (2011)
Combining active learning and reactive control for robot grasping
O. B. Kroemer;R. Detry;J. Piater;J. Peters.
Robotics and Autonomous Systems (2010)
Developing haptic and visual perceptual categories for reaching and grasping with a humanoid robot
Jefferson A. Coelho;Justus H. Piater;Roderic A. Grupen.
Robotics and Autonomous Systems (2001)
The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences
Pierre F. Gabriel;Jacques Verly;Justus Piater;Alain Genon.
Multi-camera people tracking by collaborative particle filters and principal axis-based integration
Wei Du;Justus Piater.
asian conference on computer vision (2007)
Affordances in Psychology, Neuroscience, and Robotics: A Survey
Lorenzo Jamone;Emre Ugur;Angelo Cangelosi;Luciano Fadiga.
IEEE Transactions on Cognitive and Developmental Systems (2018)
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus
Jens Forster;Christoph Schmidt;Thomas Hoyoux;Oscar Koller.
language resources and evaluation (2012)
Profile was last updated on December 6th, 2021.
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