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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 ...

Machine Learning-Aided Chronic Kidney Disease Diagnosis Based on Ultrasound Imaging Integrated with Computer-Extracted Measurable Features.

Journal of digital imaging
Although ultrasound plays an important role in the diagnosis of chronic kidney disease (CKD), image interpretation requires extensive training. High operator variability and limited image quality control of ultrasound images have made the application...

Simple, fast, and flexible framework for matrix completion with infinite width neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Matrix completion problems arise in many applications including recommendation systems, computer vision, and genomics. Increasingly larger neural networks have been successful in many of these applications but at considerable computational costs. Rem...

Can a computer "learn" nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processes.

Journal of chromatography. A
The design and optimization of chromatographic processes is essential for enabling efficient separations. To this end, hyperbolic partial differential equations (PDEs) along with nonlinear adsorption isotherms must be solved using computationally exp...

Neuromorphic computing for content-based image retrieval.

PloS one
Neuromorphic computing mimics the neural activity of the brain through emulating spiking neural networks. In numerous machine learning tasks, neuromorphic chips are expected to provide superior solutions in terms of cost and power efficiency. Here, w...

An Efficient Memristor-Based Circuit Implementation of Squeeze-and-Excitation Fully Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
Recently, there has been a surge of interest in applying memristors to hardware implementations of deep neural networks due to various desirable properties of the memristor, such as nonvolativity, multivalue, and nanosize. Most existing neural networ...

Computer Vision Positioning and Local Obstacle Avoidance Optimization Based on Neural Network Algorithm.

Computational intelligence and neuroscience
Due to the rapid development of social computerization and smart devices, there is an increasing demand for indoor positioning of mobile robots in the robotics field, so it is very important to realize the autonomous navigation of mobile robots. Howe...

Human-Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks.

Computational intelligence and neuroscience
Emotions play an essential role in human relationships, and many real-time applications rely on interpreting the speaker's emotion from their words. Speech emotion recognition (SER) modules aid human-computer interface (HCI) applications, but they ar...

Human-Computer Interaction for Recognizing Speech Emotions Using Multilayer Perceptron Classifier.

Journal of healthcare engineering
Human-computer interaction (HCI) has seen a paradigm shift from textual or display-based control toward more intuitive control modalities such as voice, gesture, and mimicry. Particularly, speech has a great deal of information, conveying information...

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation.

Sensors (Basel, Switzerland)
A lightweight on-device liquid consumption estimation system involving an energy-aware machine learning algorithm is developed in this work. This system consists of two separate on-device neural network models that carry out liquid consumption estima...