Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection. However, their deployment on ...
Abstract: The merit in adapting a Graph Neural Network (GNN) for image analysis is that it can capture long-range dependencies between distant parts of the image. This is particularly important in ...
Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, ...
Welcome to the Food Classification project! This repository focuses on binary and multiclass classification of images belonging to 10 different food classes using Convolutional Neural Networks (CNN).
It is possible to choose the values of the model parameters for a long time, but I decided to stop on a compromise between the learning speed and test accuracy.
Studies have reported the use of photoplethysmography signals to detect atrial fibrillation; however, the use of photoplethysmography signals in classifying multiclass arrhythmias has rarely been ...
Abstract: The interest in neural networks has increased significantly, and the application of this type of machine learning is vast, ranging from natural image classification to medical image ...
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