AIMC Topic: Neural Networks, Computer

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Informing geometric deep learning with electronic interactions to accelerate quantum chemistry.

Proceedings of the National Academy of Sciences of the United States of America
Predicting electronic energies, densities, and related chemical properties can facilitate the discovery of novel catalysts, medicines, and battery materials. However, existing machine learning techniques are challenged by the scarcity of training dat...

A Rolling Bearing Fault Diagnosis Based on Conditional Depth Convolution Countermeasure Generation Networks under Small Samples.

Sensors (Basel, Switzerland)
Aiming at the problems of low fault diagnosis accuracy caused by insufficient samples and unbalanced data sample distribution in bearing fault diagnosis, this paper proposes a fault diagnosis method for rolling bearings referencing conditional deep c...

IoT and Satellite Sensor Data Integration for Assessment of Environmental Variables: A Case Study on NO.

Sensors (Basel, Switzerland)
This paper introduces a novel approach to increase the spatiotemporal resolution of an arbitrary environmental variable. This is achieved by utilizing machine learning algorithms to construct a satellite-like image at any given time moment, based on ...

SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images.

Sensors (Basel, Switzerland)
Skin cancer is a deadly disease, and its early diagnosis enhances the chances of survival. Deep learning algorithms for skin cancer detection have become popular in recent years. A novel framework based on deep learning is proposed in this study for ...

Explaining One-Dimensional Convolutional Models in Human Activity Recognition and Biometric Identification Tasks.

Sensors (Basel, Switzerland)
Due to wearables' popularity, human activity recognition (HAR) plays a significant role in people's routines. Many deep learning (DL) approaches have studied HAR to classify human activities. Previous studies employ two HAR validation approaches: sub...

Discrete Missing Data Imputation Using Multilayer Perceptron and Momentum Gradient Descent.

Sensors (Basel, Switzerland)
Data are a strategic resource for industrial production, and an efficient data-mining process will increase productivity. However, there exist many missing values in data collected in real life due to various problems. Because the missing data may re...

Recognition Method of Massage Techniques Based on Attention Mechanism and Convolutional Long Short-Term Memory Neural Network.

Sensors (Basel, Switzerland)
Identifying the massage techniques of the masseuse is a prerequisite for guiding robotic massage. It is difficult to recognize multiple consecutive massage maps with a time series for current human action recognition algorithms. To solve the problem,...

Application of Deep Learning Workflow for Autonomous Grain Size Analysis.

Molecules (Basel, Switzerland)
Traditional grain size determination in materials characterization involves microscopy images and a laborious process requiring significant manual input and human expertise. In recent years, the development of computer vision (CV) has provided an alt...

Dataset for classifying and estimating the position, orientation, and dimensions of a list of primitive objects.

BMC research notes
OBJECTIVES: Robotic systems are moving toward more interaction with the environment, which requires improving environmental perception methods. The concept of primitive objects simplified the perception of the environment and is frequently used in va...

Application of machine learning for inter turn fault detection in pumping system.

Scientific reports
Pump fault diagnosis is essential for the maintenance and safety of the device as it is an important appliance used in various major sectors. Fault diagnosis at the proper time can reduce maintenance costs and save energy. This article uses a Simulin...