AIMC Topic: Neural Networks, Computer

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Analysis of Basketball Technical Movements Based on Human-Computer Interaction with Deep Learning.

Computational intelligence and neuroscience
With the continuous development of computer technology, analysis techniques based on various types of sports data sets are also evolving. One typical representative is image-based motion recognition technology, which enables video action recognition ...

DeepLumina: A Method Based on Deep Features and Luminance Information for Color Texture Classification.

Computational intelligence and neuroscience
Color texture classification is a significant computer vision task to identify and categorize textures that we often observe in natural visual scenes in the real world. Without color and texture, it remains a tedious task to identify and recognize ob...

A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting.

Computational intelligence and neuroscience
The time series is a kind of complex structure data, which contains some special characteristics such as high dimension, dynamic, and high noise. Moreover, multivariate time series (MTS) has become a crucial study in data mining. The MTS utilizes the...

A Grey BP Neural Network-Based Model for Prediction of Court Decision Service Rate.

Computational intelligence and neuroscience
The judgment service rate is an important index to reflect the fairness of the judgment of legal cases in a certain area, which is of great significance to verify the accuracy of a court judgment. In this paper, a grey neural network model combining ...

Adversarial robustness assessment: Why in evaluation both L0 and L∞ attacks are necessary.

PloS one
There are different types of adversarial attacks and defences for machine learning algorithms which makes assessing the robustness of an algorithm a daunting task. Moreover, there is an intrinsic bias in these adversarial attacks and defences to make...

iCatcher: A neural network approach for automated coding of young children's eye movements.

Infancy : the official journal of the International Society on Infant Studies
Infants' looking behaviors are often used for measuring attention, real-time processing, and learning-often using low-resolution videos. Despite the ubiquity of gaze-related methods in developmental science, current analysis techniques usually involv...

Cervical optical coherence tomography image classification based on contrastive self-supervised texture learning.

Medical physics
BACKGROUND: Cervical cancer (CC) seriously affects the health of the female reproductive system. Optical coherence tomography (OCT) emerged as a noninvasive, high-resolution imaging technology for cervical disease detection. However, OCT image annota...

Emotion Recognition from Physiological Channels Using Graph Neural Network.

Sensors (Basel, Switzerland)
In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presente...

Deep Learning-Based Approach for Emotion Recognition Using Electroencephalography (EEG) Signals Using Bi-Directional Long Short-Term Memory (Bi-LSTM).

Sensors (Basel, Switzerland)
Emotions are an essential part of daily human communication. The emotional states and dynamics of the brain can be linked by electroencephalography (EEG) signals that can be used by the Brain-Computer Interface (BCI), to provide better human-machine ...