What are the ethical considerations related to using CNNs for social media analysis?

Feb 20, 2020 ... LeNet-5. LeNet-5 architecture is perhaps the most widely known CNN architecture. It was created by Yann LeCun in 1998 and widely used for ... 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. Nov 14, 2023 ... A Convolutional Neural Network (CNN), also known as ConvNet, is a specialized type of deep learning algorithm mainly designed for tasks that necessitate object ... Aug 16, 2024 ... Reinforcement learning. Actor-Critic method · TensorFlow agents. tf ... This tutorial demonstrates training a simple Convolutional Neural Network ... Oct 5, 2020 ... I.e. if a CNN can be used to obtain yield estimates at a lower ... machine learning, deep learning, predictive analytics. publication ... With the increase in computational parallelism and low-power Integrated Circuits (ICs) design, neuromorphic technologies and machine learning algorithms ... ... CNN; Deep neural network; RT-PCR; Computer model. Received: October 27, 2022 ... Machine Learning With Applications, 6, 100138. https://doi.org/10.1016 ... ... CNN deep feature extraction with machine learning models to classify variety of food image datasets. Date of Award, Oct 2018. Original language, English. 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 ... Aug 5, 2022 ... An integrated and hybrid approach based on deep convolutional neural network and machine learning classifiers is proposed for the accurate segmentation and ...