What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer vision
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 most cited work include:
- Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision? (238 citations)
- Random subwindows for robust image classification (212 citations)
- Combining active learning and reactive control for robot grasping (128 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (83.33%)
- Computer vision (31.71%)
- Machine learning (26.02%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (83.33%)
- Robot (24.80%)
- Machine learning (26.02%)
In recent papers he was focusing on the following fields of study:
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.
Between 2015 and 2021, his most popular works were:
- Affordances in Psychology, Neuroscience, and Robotics: A Survey (85 citations)
- Computational models of affordance in robotics: a taxonomy and systematic classification: (38 citations)
- 25 Years of CNNs: Can We Compare to Human Abstraction Capabilities? (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
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.
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