AIMC Topic: Neural Networks, Computer

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Design and experiment of a 3-DoF master device with a 2-DoF parallel mechanism for flexible ureteroscopy.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Traditional commercial master devices and specialied serial master devices meet insufficient workspace, low intuitiveness, low stiffness, and poor accuracy during master-slave mapping for robot-assisted flexible ureteroscopy (FURS).

Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials.

Journal of chemical information and modeling
Computational programs accelerate the chemical discovery processes but often need proper three-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing ...

PDC: Pearl Detection with a Counter Based on Deep Learning.

Sensors (Basel, Switzerland)
Pearl detection with a counter (PDC) in a noncontact and high-precision manner is a challenging task in the area of commercial production. Additionally, sea pearls are considered to be quite valuable, so the traditional manual counting methods are no...

HEA-Net: Attention and MLP Hybrid Encoder Architecture for Medical Image Segmentation.

Sensors (Basel, Switzerland)
The model, Transformer, is known to rely on a self-attention mechanism to model distant dependencies, which focuses on modeling the dependencies of the global elements. However, its sensitivity to the local details of the foreground information is no...

Evaluation of the Transverse Crack Depth of Rail Bottoms Based on the Ultrasonic Guided Waves of Piezoelectric Sensor Arrays.

Sensors (Basel, Switzerland)
A method based on the high-frequency ultrasonic guided waves (UGWs) of a piezoelectric sensor array is proposed to monitor the depth of transverse cracks in rail bottoms. Selecting high-frequency UGWs with a center frequency of 350 kHz can enable the...

WCNN3D: Wavelet Convolutional Neural Network-Based 3D Object Detection for Autonomous Driving.

Sensors (Basel, Switzerland)
Three-dimensional object detection is crucial for autonomous driving to understand the driving environment. Since the pooling operation causes information loss in the standard CNN, we designed a wavelet-multiresolution-analysis-based 3D object detect...

Prediction of drug-drug interaction events using graph neural networks based feature extraction.

Scientific reports
The prevalence of multi_drug therapies has been increasing in recent years, particularly among the elderly who are suffering from several diseases. However, unexpected Drug_Drug interaction (DDI) can cause adverse reactions or critical toxicity, whic...

Atom Search Optimization with the Deep Transfer Learning-Driven Esophageal Cancer Classification Model.

Computational intelligence and neuroscience
Esophageal cancer (EC) is a commonly occurring malignant tumor that significantly affects human health. Earlier recognition and classification of EC or premalignant lesions can result in highly effective targeted intervention. Accurate detection and ...

Using Decision Tree Classification and AdaBoost Classification to Build the Abnormal Data Monitoring System of Financial Accounting in Colleges and Universities.

Computational intelligence and neuroscience
In order to better solve the problems of low efficiency, large consumption of human resources, and relatively low degree of intelligence in the abnormal data monitoring system of financial accounting in colleges and universities under the background ...

Application of Neural Network with Autocorrelation in Long-Term Forecasting of Systemic Financial Risk.

Computational intelligence and neuroscience
Carrying out early warning of systemic financial risk is a prerequisite for timely adjustment of monetary policy and macroprudential policy to effectively prevent and resolve systemic financial risks. This paper constructs a systemic financial risk m...