AIMC Topic: Neural Networks, Computer

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Proposing Novel Data Analytics Method for Anatomical Landmark Identification from Endoscopic Video Frames.

Journal of healthcare engineering
BACKGROUND: The anatomical landmarks contain the characteristics that are used to guide the gastroenterologists during the endoscopy. The expert can also ensure the completion of examination with the help of the anatomical landmarks. Automatic detect...

A new automatic forecasting method based on a new input significancy test of a single multiplicative neuron model artificial neural network.

Network (Bristol, England)
The model adequacy and input significance tests have not been proposed as features for the specification of a single multiplicative neuron model artificial neural networks in the literature. Moreover, there is no systematic approach based on hypothes...

Graph Convolutional Networks for Assessment of Physical Rehabilitation Exercises.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Health professionals often prescribe patients to perform specific exercises for rehabilitation of several diseases (e.g., stroke, Parkinson, backpain). When patients perform those exercises in the absence of an expert (e.g., physicians/therapists), t...

Model-driven deep unrolling: Towards interpretable deep learning against noise attacks for intelligent fault diagnosis.

ISA transactions
Intelligent fault diagnosis (IFD) has experienced tremendous progress owing to a great deal to deep learning (DL)-based methods over the decades. However, the "black box" nature of DL-based methods still seriously hinders wide applications in industr...

DLPacker: Deep learning for prediction of amino acid side chain conformations in proteins.

Proteins
Prediction of side chain conformations of amino acids in proteins (also termed "packing") is an important and challenging part of protein structure prediction with many interesting applications in protein design. A variety of methods for packing have...

Deep Learning-based detection of psychiatric attributes from German mental health records.

International journal of medical informatics
BACKGROUND: Health care records provide large amounts of data with real-world and longitudinal aspects, which is advantageous for predictive analyses and improvements in personalized medicine. Text-based records are a main source of information in me...

Finite-time and sampled-data synchronization of complex dynamical networks subject to average dwell-time switching signal.

Neural networks : the official journal of the International Neural Network Society
This study deals with the finite-time synchronization problem of a class of switched complex dynamical networks (CDNs) with distributed coupling delays via sampled-data control. First, the dynamical model is studied with coupling delays in more detai...

A deep learning system for automated kidney stone detection and volumetric segmentation on noncontrast CT scans.

Medical physics
PURPOSE: Early detection and size quantification of renal calculi are important for optimizing treatment and preventing severe kidney stone disease. Prior work has shown that volumetric measurements of kidney stones are more informative and reproduci...

Bearing Fault Reconstruction Diagnosis Method Based on ResNet-152 with Multi-Scale Stacked Receptive Field.

Sensors (Basel, Switzerland)
The axle box in the bogie system of subway trains is a key component connecting primary damper and the axle. In order to extract deep features and large-scale fault features for rapid diagnosis, a novel fault reconstruction characteristics classifica...

Computer Vision-Based Path Planning for Robot Arms in Three-Dimensional Workspaces Using Q-Learning and Neural Networks.

Sensors (Basel, Switzerland)
Computer vision-based path planning can play a crucial role in numerous technologically driven smart applications. Although various path planning methods have been proposed, limitations, such as unreliable three-dimensional (3D) localization of objec...