AIMC Topic: Neural Networks, Computer

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Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.

Japanese journal of radiology
PURPOSE: To investigate the ability of deep learning (DL) using convolutional neural networks (CNNs) for distinguishing between normal and metastatic axillary lymph nodes on ultrasound images by comparing the diagnostic performance of radiologists.

Head and neck synthetic CT generated from ultra-low-dose cone-beam CT following Image Gently Protocol using deep neural network.

Medical physics
PURPOSE: Image guidance is used to improve the accuracy of radiation therapy delivery but results in increased dose to patients. This is of particular concern in children who need be treated per Pediatric Image Gently Protocols due to long-term risks...

Effectiveness of Artificial Neural Networks for Solving Inverse Problems in Magnetic Field-Based Localization.

Sensors (Basel, Switzerland)
Recently, indoor localization has become an active area of research. Although there are various approaches to indoor localization, methods that utilize artificially generated magnetic fields from a target device are considered to be the best in terms...

Path following Control of an Underactuated Catamaran for Recovery Maneuvers.

Sensors (Basel, Switzerland)
This paper focuses on the autonomous recovery maneuvers of an unknown underactuated practical catamaran, which returns to its initial position corresponding to the man overboard (MOB) by simply adjusting the rate of turn. This paper investigates the ...

Attention Module Magnetic Flux Leakage Linked Deep Residual Network for Pipeline In-Line Inspection.

Sensors (Basel, Switzerland)
Pipeline operational safety is the foundation of the pipeline industry. Inspection and evaluation of defects is an important means of ensuring the safe operation of pipelines. In-line inspection of Magnetic Flux Leakage (MFL) can be used to identify ...

Dynamic gesture recognition based on 2D convolutional neural network and feature fusion.

Scientific reports
Gesture recognition is one of the most popular techniques in the field of computer vision today. In recent years, many algorithms for gesture recognition have been proposed, but most of them do not have a good balance between recognition efficiency a...

Motor-related signals support localization invariance for stable visual perception.

PLoS computational biology
Our ability to perceive a stable visual world in the presence of continuous movements of the body, head, and eyes has puzzled researchers in the neuroscience field for a long time. We reformulated this problem in the context of hierarchical convoluti...

A Graph Partition-Based Large-Scale Distribution Network Reconfiguration Method.

Computational intelligence and neuroscience
This article focuses on the analysis of large-scale distribution network reconstruction fused with graph theory and graph partitioning algorithms. Graph theory and graph segmentation algorithms have been rushed by many researchers in the fields of me...

Optimal Control of Whole Network Control System Using Improved Genetic Algorithm and Information Integrity Scale.

Computational intelligence and neuroscience
WNCS (Whole network control system) is a network-based distributed control system. The control loop formed by the serial network usually includes several subcontrol systems. WNCS optimal control is a complex and multiparameter coupled highly nonlinea...

Coal Mine Safety Evaluation Based on Machine Learning: A BP Neural Network Model.

Computational intelligence and neuroscience
As the core of artificial intelligence, machine learning has strong application advantages in multi-criteria intelligent evaluation and decision-making. The level of sustainable development is of great significance to the safety evaluation of coal mi...