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A multimodal convolutional neuro-fuzzy network for emotion understanding of movie clips.

Neural networks : the official journal of the International Neural Network Society
Multimodal emotion understanding enables AI systems to interpret human emotions. With accelerated video surge, emotion understanding remains challenging due to inherent data ambiguity and diversity of video content. Although deep learning has made a ...

Robotic Sensing and Stimuli Provision for Guided Plant Growth.

Journal of visualized experiments : JoVE
Robot systems are actively researched for manipulation of natural plants, typically restricted to agricultural automation activities such as harvest, irrigation, and mechanical weed control. Extending this research, we introduce here a novel methodol...

Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2.

eNeuro
A crucial step in understanding visual input is its organization into meaningful components, in particular object contours and partially occluded background structures. This requires that all contours are assigned to either the foreground or the back...

Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection.

Neural networks : the official journal of the International Neural Network Society
Facial landmark detection is to localize multiple facial key-points for a given facial image. While many methods have achieved remarkable performance in recent years, the accuracy remains unsatisfactory due to some uncontrolled conditions such as occ...

Cognitive Action Laws: The Case of Visual Features.

IEEE transactions on neural networks and learning systems
This paper proposes a theory for understanding perceptual learning processes within the general framework of laws of nature. Artificial neural networks are regarded as systems whose connections are Lagrangian variables, namely, functions depending on...

Machine learning accurately classifies age of toddlers based on eye tracking.

Scientific reports
How people extract visual information from complex scenes provides important information about cognitive processes. Eye tracking studies that have used naturalistic, rather than highly controlled experimental stimuli, reveal that variability in looki...

Improving the Antinoise Ability of DNNs via a Bio-Inspired Noise Adaptive Activation Function Rand Softplus.

Neural computation
Although deep neural networks (DNNs) have led to many remarkable results in cognitive tasks, they are still far from catching up with human-level cognition in antinoise capability. New research indicates how brittle and susceptible current models are...

Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex.

Journal of neurophysiology
Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple cons...

Continuous learning in single-incremental-task scenarios.

Neural networks : the official journal of the International Neural Network Society
It was recently shown that architectural, regularization and rehearsal strategies can be used to train deep models sequentially on a number of disjoint tasks without forgetting previously acquired knowledge. However, these strategies are still unsati...

An unsupervised neuromorphic clustering algorithm.

Biological cybernetics
Brains perform complex tasks using a fraction of the power that would be required to do the same on a conventional computer. New neuromorphic hardware systems are now becoming widely available that are intended to emulate the more power efficient, hi...