AIMC Topic: Neural Networks, Computer

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Ageing Safely in the Digital Era: A New Unobtrusive Activity Monitoring Framework Leveraging on Daily Interactions with Hand-Operated Appliances.

Sensors (Basel, Switzerland)
Supporting the elderly to maintain their independence, safety, and well-being through Active Assisted Living (AAL) technologies, is gaining increasing momentum. Recently, Non-intrusive Load Monitoring (NILM) approaches have become the focus of these ...

Lean Neural Networks for Autonomous Radar Waveform Design.

Sensors (Basel, Switzerland)
In recent years, neural networks have exploded in popularity, revolutionizing the domains of computer vision, natural language processing, and autonomous systems. This is due to neural networks ability to approximate complex non-linear functions. Des...

A New Method of Image Classification Based on Domain Adaptation.

Sensors (Basel, Switzerland)
Deep neural networks can learn powerful representations from massive amounts of labeled data; however, their performance is unsatisfactory in the case of large samples and small labels. Transfer learning can bridge between a source domain with rich s...

Comparative Study of Machine-Learning Frameworks for the Elaboration of Feed-Forward Neural Networks by Varying the Complexity of Impedimetric Datasets Synthesized Using Eddy Current Sensors for the Characterization of Bi-Metallic Coins.

Sensors (Basel, Switzerland)
A suitable framework for the development of artificial neural networks is important because it decides the level of accuracy, which can be reached for a certain dataset and increases the certainty about the reached classification results. In this pap...

DOA Estimation Method Based on Improved Deep Convolutional Neural Network.

Sensors (Basel, Switzerland)
For the multi-target DOA estimation problem of uniform linear arrays, this paper proposes a DOA estimation method based on the deep convolution neural network. The algorithm adopts the deep convolutional neural network, and the DOA estimation problem...

Detection and identification of tea leaf diseases based on AX-RetinaNet.

Scientific reports
The accurate detection and identification of tea leaf diseases are conducive to its precise prevention and control. Convolutional neural network (CNN) can automatically extract the features of diseased tea leaves in the images. However, tea leaf imag...

A backbone-centred energy function of neural networks for protein design.

Nature
A protein backbone structure is designable if a substantial number of amino acid sequences exist that autonomously fold into it. It has been suggested that the designability of backbones is governed mainly by side chain-independent or side chain type...

NIFtHool: an informatics program for identification of NifH proteins using deep neural networks.

F1000Research
Atmospheric nitrogen fixation carried out by microorganisms has environmental and industrial importance, related to the increase of soil fertility and productivity. The present work proposes the development of a new high precision system that allows ...

Compound W-Net with Fully Accumulative Residual Connections for Liver Segmentation Using CT Images.

Computational and mathematical methods in medicine
Computed tomography (CT) is a common modality for liver diagnosis, treatment, and follow-up process. Providing accurate liver segmentation using CT images is a crucial step towards those tasks. In this paper, we propose a stacked 2-U-Nets model with ...

Research on Robot Fuzzy Neural Network Motion System Based on Artificial Intelligence.

Computational intelligence and neuroscience
An intelligent controller based on a self-learning interval type-II fuzzy neural network is proposed to make the motion controller of the industrial intelligent robot with good adaptability. This controller has a parallel structure and contains an in...