What are some ethical considerations related to the use of CNNs in image analysis?

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. Aug 15, 2022 ... What neural network is appropriate for your predictive modeling problem? It can be difficult for a beginner to the field of deep learning to ... In this paper, three prediction algorithms have been proposed which will predict the protein secondary structure based on machine learning. A convolutional neural network (CNN or ConvNet) is a network architecture for deep learning that learns directly from data. 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 ... Jan 23, 2023 ... Comparing the performance of various CNNs and machine learning methods in diagnosing three types of brain tumors revealed that the 2D CNN ... A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep ... Mar 25, 2023 ... In this paper, we compared and explored the two methodologies on the DEMoS dataset consisting of 8869 audio files of 58 speakers in different emotional states. This theoretical spotlights on creating iris distinguishing proof frameworks using machine learning and CNN-based image processing. ... CNN Based Image 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 ...