What are some applications of CNNs in scientific research?

What is a Convolutional Neural Network? In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a ... Mar 31, 2021 ... This review attempts to provide a more comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field. Mar 25, 2025 ... We introduce CNN-TumorNet, an innovative method for brain tumor classification utilizing a deep convolutional neural network (CNN) for the ... Augmented graph representations are further input to a custom CNN deep learning architecture with a split of 70% train, 10% validation and 20% test ... CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production. Electric Power Systems Research, 2022, 208 ... Jan 21, 2021 ... In machine learning, each type of artificial neural network is tailored to perform certain sets of tasks. In order to explain these tasks and ... Abstract. We present Point-Voxel CNN (PVCNN) for efficient, fast 3D deep learning. Previous work processes 3D data using either voxel-based or point-based NN ... Jun 27, 2017 ... The convolution in a CNN is going to be the kernel g of which we will learn some weights in order to extract the information we need and then perhaps apply an ... The basic CNN architecture consists of five main layers: input, convolutional, activation, pooling, and fully connected. Each layer plays a specific role in ... Complex problems can be solved and objects can be recognized in images based on the Google TensorFlow ™ library - a widely used deep learning framework. Based ...