AIMC Topic: Neural Networks, Computer

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Automatic detection and classification of manufacturing defects in metal boxes using deep neural networks.

PloS one
This paper develops a new machine vision framework for efficient detection and classification of manufacturing defects in metal boxes. Previous techniques, which are based on either visual inspection or on hand-crafted features, are both inaccurate a...

Pectin extraction from Helianthus annuus (sunflower) heads using RSM and ANN modelling by a genetic algorithm approach.

International journal of biological macromolecules
In this work, Response Surface Methodology (RSM) and Artificial Neural Network coupled with genetic algorithm (ANN-GA) have been used to develop a model and optimise the conditions for the extraction of pectin from sunflower heads. Input parameters w...

Computer vs human: Deep learning versus perceptual training for the detection of neck of femur fractures.

Journal of medical imaging and radiation oncology
INTRODUCTION: To evaluate the accuracy of deep convolutional neural networks (DCNNs) for detecting neck of femur (NoF) fractures on radiographs, in comparison with perceptual training in medically-naïve individuals.

Neuroevolution of a Modular Memory-Augmented Neural Network for Deep Memory Problems.

Evolutionary computation
We present Modular Memory Units (MMUs), a new class of memory-augmented neural network. MMU builds on the gated neural architecture of Gated Recurrent Units (GRUs) and Long Short Term Memory (LSTMs), to incorporate an external memory block, similar t...

Multiregion segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks.

Medical physics
PURPOSE: Precise segmentation of bladder walls and tumor regions is an essential step toward noninvasive identification of tumor stage and grade, which is critical for treatment decision and prognosis of patients with bladder cancer (BC). However, th...

Performance assessment of artificial neural networks and support vector regression models for stream flow predictions.

Environmental monitoring and assessment
Water resources planning, development, and management need reliable forecasts of river flows. In past few decades, an important dimension has been introduced in the prediction of the hydrologic phenomenon through artificial intelligence-based modelin...

Fully tuned RBF neural network controller for ultrasound hyperthermia cancer tumour therapy.

Network (Bristol, England)
Thermal dose is an important clinical efficacy index for hyperthermia cancer treatment. This paper presents a new direct radial basis function (RBF) neural network controller for high-temperature hyperthermia thermal dose during the therapeutic proce...

Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.

Environmental science and pollution research international
River water temperature is a key control of many physical and bio-chemical processes in river systems, which theoretically depends on multiple factors. Here, four different machine learning models, including multilayer perceptron neural network model...

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks.

Scientific reports
Magnetic resonance imaging (MRI) has been proposed as a complimentary method to measure bone quality and assess fracture risk. However, manual segmentation of MR images of bone is time-consuming, limiting the use of MRI measurements in the clinical p...