AIMC Topic: Neural Networks, Computer

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Accelerated construction of stress relief music datasets using CNN and the Mel-scaled spectrogram.

PloS one
Listening to music is a crucial tool for relieving stress and promoting relaxation. However, the limited options available for stress-relief music do not cater to individual preferences, compromising its effectiveness. Traditional methods of curating...

Sequential safe static and dynamic screening rule for accelerating support tensor machine.

Neural networks : the official journal of the International Neural Network Society
Support tensor machine (STM), as a higher-order extension of support vector machine, is adept at effectively addressing tensorial data classification problems, which maintains the inherent structure in tensors and mitigates the curse of dimensionalit...

Multi-grained visual pivot-guided multi-modal neural machine translation with text-aware cross-modal contrastive disentangling.

Neural networks : the official journal of the International Neural Network Society
The goal of multi-modal neural machine translation (MNMT) is to incorporate language-agnostic visual information into text to enhance the performance of machine translation. However, due to the inherent differences between image and text, these two m...

Temporal prediction of suicidal ideation in an ecological momentary assessment study with recurrent neural networks.

Journal of affective disorders
INTRODUCTION: Ecological Momentary Assessment (EMA) holds promise for providing insights into daily life experiences when studying mental health phenomena. However, commonly used mixed-effects linear statistical models do not fully utilize the richne...

Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate.

Artificial intelligence in medicine
We present a neural network framework for learning a survival model to predict a time-to-event outcome while simultaneously learning a topic model that reveals feature relationships. In particular, we model each subject as a distribution over "topics...

Fast synchronization control and application for encryption-decryption of coupled neural networks with intermittent random disturbance.

Neural networks : the official journal of the International Neural Network Society
In this paper, we design a new class of coupled neural networks with stochastically intermittent disturbances, in which the perturbation mechanism is different from other existed random neural networks. It is significant to construct the new models, ...

Masked hypergraph learning for weakly supervised histopathology whole slide image classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Graph neural network (GNN) has been extensively used in histopathology whole slide image (WSI) analysis due to the efficiency and flexibility in modelling relationships among entities. However, most existing GNN-based WSI a...

Systematic training of table tennis players' physical performance based on artificial intelligence technology and data fusion of sensing devices.

SLAS technology
This research emphasises the value of physical training for table tennis players, particularly as ball speed and spin rate decline and emphasises how important intensity quality is to the game. Chinese table tennis players' dual identities place grea...

Understanding Human Cognition Through Computational Modeling.

Topics in cognitive science
One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an essential role in providing theoretical explanations and predictions of human behav...

FP-GCN: Frequency Pyramid Graph Convolutional Network for Enhancing Pathological Gait Classification.

Sensors (Basel, Switzerland)
Gait, a manifestation of one's walking pattern, intricately reflects the harmonious interplay of various bodily systems, offering valuable insights into an individual's health status. However, the current study has shortcomings in the extraction of t...