AIMC Topic: Neural Networks, Computer

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Automatic dental biofilm detection based on deep learning.

Journal of clinical periodontology
AIM: To estimate the automated biofilm detection capacity of the U-Net neural network on tooth images.

Leveraging joint incremental learning objective with data ensemble for class incremental learning.

Neural networks : the official journal of the International Neural Network Society
A class-incremental learning problem is characterized by training data becoming available in a phase-by-phase manner. Deep learning models suffer from catastrophic forgetting of the classes in the older phases as they get trained on the classes intro...

Quasi-synchronization of drive-response systems with parameter mismatch via event-triggered impulsive control.

Neural networks : the official journal of the International Neural Network Society
In this paper, an event-triggered impulsive control method is proposed to investigate the quasi-synchronization of drive-response systems with parameter mismatch, which integrates the event-triggered control and impulsive control together. The impuls...

Compatible-domain Transfer Learning for Breast Cancer Classification with Limited Annotated Data.

Computers in biology and medicine
Microscopic analysis of breast cancer images is the primary task in diagnosing cancer malignancy. Recent attempts to automate this task have employed deep learning models whose success has depended on large volumes of data, while acquiring annotated ...

Detection of the separated root canal instrument on panoramic radiograph: a comparison of LSTM and CNN deep learning methods.

Dento maxillo facial radiology
OBJECTIVES: A separated endodontic instrument is one of the challenging complications of root canal treatment. The purpose of this study was to compare two deep learning methods that are convolutional neural network (CNN) and long short-term memory (...

CNN-RNN Network Integration for the Diagnosis of COVID-19 Using Chest X-ray and CT Images.

Sensors (Basel, Switzerland)
The 2019 coronavirus disease (COVID-19) has rapidly spread across the globe. It is crucial to identify positive cases as rapidly as humanely possible to provide appropriate treatment for patients and prevent the pandemic from spreading further. Both ...

As good as human experts in detecting plant roots in minirhizotron images but efficient and reproducible: the convolutional neural network "RootDetector".

Scientific reports
Plant roots influence many ecological and biogeochemical processes, such as carbon, water and nutrient cycling. Because of difficult accessibility, knowledge on plant root growth dynamics in field conditions, however, is fragmentary at best. Minirhiz...

Optimal control by deep learning techniques and its applications on epidemic models.

Journal of mathematical biology
We represent the optimal control functions by neural networks and solve optimal control problems by deep learning techniques. Adjoint sensitivity analysis is applied to train the neural networks embedded in differential equations. This method can not...

Volleyball Movement Standardization Recognition Model Based on Convolutional Neural Network.

Computational intelligence and neuroscience
Artificial intelligence and deep learning have attracted much attention from researchers in industry and academia. The volleyball movement standardization and recognition model involve the application of artificial intelligence and deep learning. In ...

The ecological discourse analysis of news discourse based on deep learning from the perspective of ecological philosophy.

PloS one
Recently, ecological damage and environmental pollution have become increasingly serious. Experts in various fields have started to study related issues from diverse points of view. To prevent the accelerated deterioration of the ecological environme...