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pro vyhledávání: '"Hamker, Fred H."'
Humans can quickly adapt their behavior to changes in the environment. Classical reversal learning tasks mainly measure how well participants can disengage from a previously successful behavior but not how alternative responses are explored. Here, we
Automatic processing of emotion information through deep neural networks (DNN) can have great benefits (e.g., for human-machine interaction). Vice versa, machine learning can profit from concepts known from human information processing (e.g., visual
How do robots learn to perform motor tasks in a specific condition and apply what they have learned in a new condition? This paper proposes a framework for motor coordination acquisition of a robot drawing straight lines within a part of the workspac
Publikováno v:
Front. Comput. Neurosci., 25 March 2015 | doi: 10.3389/fncom.2015.00035
A substantial number of works have aimed at modeling the receptive field properties of the primary visual cortex (V1). Their evaluation criterion is usually the similarity of the model response properties to the recorded responses from biological org
Autor:
Ziesche, Arnold, Hamker, Fred H.
Publikováno v:
Ziesche A and Hamker FH (2014) Brain circuits underlying visual stability across eye movements—converging evidence for a neuro-computational model of area LIP. Front. Comput. Neurosci. 8:25. doi: 10.3389/fncom.2014.00025
The understanding of the subjective experience of a visually stable world despite the occurrence of an observer's eye movements has been the focus of extensive research for over 20 years. These studies have revealed fundamental mechanisms such as ant
Autor:
Vitay, Julien, Hamker, Fred H.
Publikováno v:
Vitay J and Hamker FH (2014) Timing and expectation of reward: a neuro-computational model of the afferents to the ventral tegmental area. Front. Neurorobot. 8:4. doi: 10.3389/fnbot.2014.00004
Neural activity in dopaminergic areas such as the ventral tegmental area is influenced by timing processes, in particular by the temporal expectation of rewards during Pavlovian conditioning. Receipt of a reward at the expected time allows to compute
In real world scenarios, objects are often partially occluded. This requires a robustness for object recognition against these perturbations. Convolutional networks have shown good performances in classification tasks. The learned convolutional filte
Externí odkaz:
http://arxiv.org/abs/1912.03201
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Autor:
Burkhardt, Micha, Bergelt, Julia, Gönner, Lorenz, Dinkelbach, Helge Ülo, Beuth, Frederik, Schwarz, Alex, Bicanski, Andrej, Burgess, Neil, Hamker, Fred H.
Publikováno v:
In Neural Networks October 2023 167:473-488
Autor:
Baladron, Javier, Hamker, Fred H.
Publikováno v:
Cognitive Computation; Sep2024, Vol. 16 Issue 5, p2405-2410, 6p