Abstract: The objective of this project is to classify the four types of soil images using deep learning models that is the Convolutional Neural Networks (CNN) and the Artificial Neural Networks (ANN) ...
bCentre for Translational Bioinformatics, William Harvey Research Institute, London, UK cExperimental Medicine and Rheumatology, William Harvey Research Institute, London, UK dSchool of Infection, ...
The survey was conducted both online and by telephone from August 21 through September 1. The 2,077 adults who took the poll were selected from two sample sources – the SSRS Opinion Panel and a list ...
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive ...
1 Eye Hospital, The First Affiliated Hospital of Harbin Medical University, Harbin, China 2 School of Intelligent Science and Engineering, Harbin Engineering University, Harbin, China Background: As a ...
1 National Engineering School of Sfax (ENIS), University of Sfax, Sfax, Tunisia 2 Multimedia, Information Systems and Advanced Computing Laboratory (MIRACL), University of Sfax, Sfax, Tunisia ...
classify.py is the main python file that trains the model to recognise different types of bears by learning from images We use a neural network (CNN) here to look at 50-100 images of each type of bear ...
A group of scientists led by researchers from the University of New South Wales (UNSW) in Australia has developed a novel deep-learning method for denoising outdoor electroluminescence (EL) images of ...
Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback