How can we encourage responsible innovation and discourage the misuse of CNN technology?

Feb 10, 2020 ... The main novelty of this study was to build a coupled CNN–LSTM model to predict water quality variables. Two traditional machine learning models ... Current approaches to object recognition make essential use of machine learning methods. To im- prove their performance, we can collect larger datasets, learn ... Oct 17, 2024 ... Deep learning-based anomaly detection using one-dimensional convolutional neural networks (1D CNN) in machine centers (MCT) and computer numerical control (CNC ... The objective of this paper is using deep learning to uncover higher-level representational features, to clearly explain transfer learning, to provide current ... A convolutional neural network is a type of deep learning algorithm that is most often applied to analyze and learn visual features from large amounts of data. A convolutional neural network (CNN or ConvNet) is a network architecture for deep learning that learns directly from data. A regional wind wave prediction surrogate model based on CNN deep learning network ... In recent years, machine learning methods have gradually been ... A convolutional neural network (CNN) is a type of artificial neural network used primarily for image recognition and processing. 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 ... 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.