Orienting Attention Based on Long-Term Memory Improves Perceptual Discriminations [PDF]
, 2009 The role of attentional orienting in daily life is to selectively deploy both behavioural and neural resources towards events, based on continually changing task goals and expectations, in order to optimize performance.
Anling Rao +3 more
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Comparison and combination of gamified neurofeedback training and general behavioral training.
PLoS ONE, 2022 With the rapid development of the international community, foreign language learning has become increasingly important. Listening training is a particularly important component of foreign language learning. The most difficult aspect of listening training
Ming Chang +4 more
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Reversal of a Spatial Discrimination Task in the Common Octopus (Octopus vulgaris)
Frontiers in Behavioral Neuroscience, 2021 Reversal learning requires an animal to learn to discriminate between two stimuli but reverse its responses to these stimuli every time it has reached a learning criterion.
Alexander Bublitz +2 more
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Better, Not Just More—Contrast in Qualitative Aspects of Reward Facilitates Impulse Control in Pigs
Frontiers in Psychology, 2018 Delay-of-gratification paradigms, such as the famous “Marshmallow Test,” are designed to investigate the complex cognitive concepts of self-control and impulse control in humans and animals. Such tests determine whether a subject will demonstrate impulse
Manuela Zebunke +8 more
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Overtraining Strengthens the Visual Discrimination Memory Trace Outside the Hippocampus in Male Rats
Frontiers in Behavioral Neuroscience, 2021 The hippocampus (HPC) may compete with other memory systems when establishing a representation, a process termed overshadowing. However, this overshadowing may be mitigated by repeated learning episodes, making a memory resistant to post-training ...
Hugo Lehmann +2 more
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Discriminately decreasing discriminability with learned image filters [PDF]
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012 In machine learning and computer vision, input images are often filtered to increase data discriminability. In some situations, however, one may wish to purposely decrease discriminability of one classification task (a "distractor" task), while simultaneously preserving information relevant to another (the task-of-interest): For example, it may be ...
Whitehill, Jacob, Movellan, Javier
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Classification of Dead Cocoons Using Convolutional Neural Networks and Machine Learning Methods
IEEE Access, 2023 Image recognition methods classify or categorize objects by extracting significant properties from digital images of the objects and are used in the field of agriculture for quality determination.
Ahyeong Lee +4 more
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Using giant african pouched rats to detect human tuberculosis: a review
The Pan African Medical Journal, 2015 Despite its characteristically low sensitivity, sputum smear microscopy remains the standard for diagnosing tuberculosis (TB) in resource-poor countries. In an attempt to develop an alternative or adjunct to microscopy, researchers have recently examined
Alan Poling +6 more
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Lack of Pattern Separation in Sensory Inputs to the Olfactory Bulb during Perceptual Learning. [PDF]
, 2017 Recent studies revealed changes in odor representations in the olfactory bulb during active olfactory learning (Chu et al., 2016; Yamada et al., 2017).
Chu, Monica W +2 more
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Generative-Discriminative Complementary Learning
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 The majority of state-of-the-art deep learning methods are discriminative approaches, which model the conditional distribution of labels given inputs features. The success of such approaches heavily depends on high-quality labeled instances, which are not easy to obtain, especially as the number of candidate classes increases.
Xu, Yanwu +5 more
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