AIMC Topic: Neural Networks, Computer

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Neural networks with ReLU powers need less depth.

Neural networks : the official journal of the International Neural Network Society
Despite the widespread success of deep learning in various applications, neural network theory has been lagging behind. The choice of the activation function plays a critical role in the expressivity of a neural network but for reasons that are not y...

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data.

Behavior research methods
We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using on...

Ultra-wide field and new wide field composite retinal image registration with AI-enabled pipeline and 3D distortion correction algorithm.

Eye (London, England)
PURPOSE: This study aimed to compare a new Artificial Intelligence (AI) method to conventional mathematical warping in accurately overlaying peripheral retinal vessels from two different imaging devices: confocal scanning laser ophthalmoscope (cSLO) ...

Effects of CO concentration and time on algal biomass film, NO3-N concentration, and pH in the membrane bioreactor: Simulation-based ANN, RSM and NSGA-II.

Journal of environmental management
The practice of aquaculture is associated with the generation of a substantial quantity of effluent. Microalgae must effectively assimilate nitrogen and phosphorus from their surrounding environment for growth. This study modeled the algal biomass fi...

A Deep Learning Model for Detecting Rhegmatogenous Retinal Detachment Using Ophthalmologic Ultrasound Images.

Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde
INTRODUCTION: Rhegmatogenous retinal detachment (RRD) is one of the most common fundus diseases. Many rural areas of China have few ophthalmologists, and ophthalmologic ultrasound examination is of great significance for remote diagnosis of RRD. Ther...

BioEGRE: a linguistic topology enhanced method for biomedical relation extraction based on BioELECTRA and graph pointer neural network.

BMC bioinformatics
BACKGROUND: Automatic and accurate extraction of diverse biomedical relations from literature is a crucial component of bio-medical text mining. Currently, stacking various classification networks on pre-trained language models to perform fine-tuning...

A new convolutional neural network based on combination of circlets and wavelets for macular OCT classification.

Scientific reports
Artificial intelligence (AI) algorithms, encompassing machine learning and deep learning, can assist ophthalmologists in early detection of various ocular abnormalities through the analysis of retinal optical coherence tomography (OCT) images. Despit...

An improved human activity recognition technique based on convolutional neural network.

Scientific reports
A convolutional neural network (CNN) is an important and widely utilized part of the artificial neural network (ANN) for computer vision, mostly used in the pattern recognition system. The most important applications of CNN are medical image analysis...

Fine-tuning coreference resolution for different styles of clinical narratives.

Journal of biomedical informatics
OBJECTIVE: Coreference resolution (CR) is a natural language processing (NLP) task that is concerned with finding all expressions within a single document that refer to the same entity. This makes it crucial in supporting downstream NLP tasks such as...

Design and Development of an Imitation Detection System for Human Action Recognition Using Deep Learning.

Sensors (Basel, Switzerland)
Human action recognition (HAR) is a rapidly growing field with numerous applications in various domains. HAR involves the development of algorithms and techniques to automatically identify and classify human actions from video data. Accurate recognit...