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A neural network model of the effect of prior experience with regularities on subsequent category learning.

Cognition
Categories are often structured by the similarities of instances within the category defined across dimensions or features. Researchers typically assume that there is a direct, linear relationship between the physical input dimensions across which ca...

Learning to Compose and Reason with Language Tree Structures for Visual Grounding.

IEEE transactions on pattern analysis and machine intelligence
Grounding natural language in images, such as localizing "the black dog on the left of the tree", is one of the core problems in artificial intelligence, as it needs to comprehend the fine-grained language compositions. However, existing solutions me...

A deep neural network model for multi-view human activity recognition.

PloS one
Multiple cameras are used to resolve occlusion problem that often occur in single-view human activity recognition. Based on the success of learning representation with deep neural networks (DNNs), recent works have proposed DNNs models to estimate hu...

Disentangled Representation Learning for Multiple Attributes Preserving Face Deidentification.

IEEE transactions on neural networks and learning systems
Face is one of the most attractive sensitive information in visual shared data. It is an urgent task to design an effective face deidentification method to achieve a balance between facial privacy protection and data utilities when sharing data. Most...

Multipath Cross Graph Convolution for Knowledge Representation Learning.

Computational intelligence and neuroscience
In the past, most of the entity prediction methods based on embedding lacked the training of local core relationships, resulting in a deficiency in the end-to-end training. Aiming at this problem, we propose an end-to-end knowledge graph embedding re...

Clustering by Errors: A Self-Organized Multitask Learning Method for Acoustic Scene Classification.

Sensors (Basel, Switzerland)
Acoustic scene classification (ASC) tries to inference information about the environment using audio segments. The inter-class similarity is a significant issue in ASC as acoustic scenes with different labels may sound quite similar. In this paper, t...

Application of Multilayer Perceptron Genetic Algorithm Neural Network in Chinese-English Parallel Corpus Noise Processing.

Computational intelligence and neuroscience
This paper uses neural network as a predictive model and genetic algorithm as an online optimization algorithm to simulate the noise processing of Chinese-English parallel corpus. At the same time, according to the powerful random global search mecha...

A Multi-RNN Research Topic Prediction Model Based on Spatial Attention and Semantic Consistency-Based Scientific Influence Modeling.

Computational intelligence and neuroscience
Computer science discipline includes many research fields, which mutually influence and promote each other's development. This poses two great challenges of predicting the research topics of each research field. One is how to model fine-grained topic...

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials.

Communications biology
Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. Howeve...

End-to-End Autonomous Exploration with Deep Reinforcement Learning and Intrinsic Motivation.

Computational intelligence and neuroscience
Developing artificial intelligence (AI) agents is challenging for efficient exploration in visually rich and complex environments. In this study, we formulate the exploration question as a reinforcement learning problem and rely on intrinsic motivati...