AIMC Topic: Neural Networks, Computer

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Application of ANN and SVM for prediction nutrients in rivers.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
This paper presents the results of predicting nutrients in rivers on national level by the use of two artificial intelligence methodologies. Artificial neural network (ANN) and support vector machine (SVM) were used to predict annual concentration of...

Periodic event-triggered sliding mode control for lower limb exoskeleton based on human-robot cooperation.

ISA transactions
This paper presents a periodic event-triggered sliding mode control (SMC) scheme based on human-robot cooperation for lower limb exoskeletons. Firstly, a Genetic Algorithm-Back propagation (GA-BP) neural network is proposed to estimate the motion int...

Current directions in combining simulation-based macromolecular modeling approaches with deep learning.

Expert opinion on drug discovery
: Structure-guided drug discovery relies on accurate computational methods for modeling macromolecules. Simulations provide means of predicting macromolecular folds, of discovering function from structure, and of designing macromolecules to serve as ...

Searching collaborative agents for multi-plane localization in 3D ultrasound.

Medical image analysis
3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multiple standard planes (SPs) in one shot. Thus, automatically localizing SPs in 3D US has the potential t...

Functional link convolutional neural network for the classification of diabetes mellitus.

International journal for numerical methods in biomedical engineering
Diabetes is a faction of metabolic ailments distinguished by hyperglycemia which is the consequence of a defect, in the action of insulin, insulin secretion, or both and producing various abnormalities in the human body. In recent years, the utilizat...

Real-Time Environment Monitoring Using a Lightweight Image Super-Resolution Network.

International journal of environmental research and public health
Deep-learning (DL)-based methods are of growing importance in the field of single image super-resolution (SISR). The practical application of these DL-based models is a remaining problem due to the requirement of heavy computation and huge storage re...

Neural networks for increased accuracy of allergenic pollen monitoring.

Scientific reports
Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in imag...

Comparison of cephalometric measurements between conventional and automatic cephalometric analysis using convolutional neural network.

Progress in orthodontics
OBJECTIVE: The rapid development of artificial intelligence technologies for medical imaging has recently enabled automatic identification of anatomical landmarks on radiographs. The purpose of this study was to compare the results of an automatic ce...

An Effective Method for Detecting and Classifying Diabetic Retinopathy Lesions Based on Deep Learning.

Computational and mathematical methods in medicine
Diabetic retinopathy occurs as a result of the harmful effects of diabetes on the eyes. Diabetic retinopathy is also a disease that should be diagnosed early. If not treated early, vision loss may occur. It is estimated that one third of more than ha...