This article discusses a new mixed model for obtaining dynamometer data from pumping units in oil fields. The model uses motor electrical parameter data…
Browsing: Convolutional Neural Network
This article discusses various methods for segmenting cervical cells, including those based on similarity of adjacent pixels, iterative threshold and regularization level set algorithms,…
Chinese researchers have developed a deep learning method to enhance image quality in metalens cameras, making it possible for them to be integrated into…
This article discusses the use of electric network frequency (ENF) as a reliable technique in audio forensics and introduces a blind audio forensics framework,…
A deep learning model using transthoracic echocardiograms (TTEs) can accurately predict patients with active or occult atrial fibrillation (AF). The model was trained on…
Edgecelsior founder Pete Bernard has been pushing the envelope of edge computing for years and believes that the combination of generative artificial intelligence (GenAI)…
An end-to-end deep learning model, DLPGA, has been proposed for predicting peak ground acceleration (PGA) in earthquake early warning systems. The model uses a…
The article discusses a novel Raman spectral preprocessing model, RSBPCNN, which uses a patches strategy and self-supervision strategy to improve feature learning ability and…
This thesis explores the potential of leveraging recent technological innovations to accelerate taxonomic research, which is a critical bottleneck in the current sixth mass…
This paper provides a comprehensive study of the application of convolutional neural networks (CNNs) in the classification of human activity recognition (HAR) tasks. It…