AIMC Topic: Neural Networks, Computer

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Introducing a Novel Model-Free Multivariable Adaptive Neural Network Controller for Square MIMO Systems.

Sensors (Basel, Switzerland)
In this study, a novel Multivariable Adaptive Neural Network Controller (MANNC) is developed for coupled model-free n-input n-output systems. The learning algorithm of the proposed controller does not rely on the model of a system and uses only the h...

Image Synthesis Pipeline for CNN-Based Sensing Systems.

Sensors (Basel, Switzerland)
The rapid development of machine learning technologies in recent years has led to the emergence of CNN-based sensors or ML-enabled smart sensor systems, which are intensively used in medical analytics, unmanned driving of cars, Earth sensing, etc. In...

An efficient self-attention network for skeleton-based action recognition.

Scientific reports
There has been significant progress in skeleton-based action recognition. Human skeleton can be naturally structured into graph, so graph convolution networks have become the most popular method in this task. Most of these state-of-the-art methods op...

Automated pancreas segmentation and volumetry using deep neural network on computed tomography.

Scientific reports
Pancreas segmentation is necessary for observing lesions, analyzing anatomical structures, and predicting patient prognosis. Therefore, various studies have designed segmentation models based on convolutional neural networks for pancreas segmentation...

Identifying key differences between linear stochastic estimation and neural networks for fluid flow regressions.

Scientific reports
Neural networks (NNs) and linear stochastic estimation (LSE) have widely been utilized as powerful tools for fluid-flow regressions. We investigate fundamental differences between them considering two canonical fluid-flow problems: (1) the estimation...

Collection of 2429 constrained headshots of 277 volunteers for deep learning.

Scientific reports
Deep learning has rapidly been filtrating many aspects of human lives. In particular, image recognition by convolutional neural networks has inspired numerous studies in this area. Hardware and software technologies as well as large quantities of dat...

A deep learning framework for automated detection and quantitative assessment of liver trauma.

BMC medical imaging
BACKGROUND: Both early detection and severity assessment of liver trauma are critical for optimal triage and management of trauma patients. Current trauma protocols utilize computed tomography (CT) assessment of injuries in a subjective and qualitati...

Optimization of a Deep Learning Algorithm for Security Protection of Big Data from Video Images.

Computational intelligence and neuroscience
With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy dis...

Hotel Review Classification Based on the Text Pretraining Heterogeneous Graph Neural Network Model.

Computational intelligence and neuroscience
With the amount of online information continuously growing, it becomes more and more important for online stores to recommend corresponding products precisely based on users' preferences. Reviews for various products can be of great help for the reco...

Learning Feature Channel Weighting for Real-Time Visual Tracking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recently, the siamese convolutional neural network plays an important role in the field of visual tracking, which can obtain high tracking accuracy and good real-time performance. However, the requirement of offline training a specific neural network...