What are the key principles of responsible AI development and deployment?

Jun 28, 2021 ... Fast R-CNN brings feature extraction and region selection into a single machine learning model. Fast R-CNN receives an image and a set of ... Feb 8, 2022 ... ... Machine Learning, Stockholm, Sweden, PMLR 80 1–19 (2018) ... Random CNN structure: tool to increase generalization ability in deep learning. We have proposed a deep learning method called BCM-SegNet, an optimized Mask R-CNN-based algorithm for segmenting BSE images of bronze casting moulds and cores. Jul 21, 2022 ... Predicting wind power generation using machine learning and CNN-LSTM approaches ... Hyperparameters are adjusted using all the machine learning ... Mar 28, 2024 ... SANS-CNN is designed specifically for astronaut ophthalmic health and demonstrates robust detection of SANS-like conditions when compared to ... Feb 1, 2023 ... Convolutional Neural Networks (CNNs) is a powerful deep learning architecture well-suited to image classification and object recognition tasks. 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 ... The basic CNN architecture consists of five main layers: input, convolutional, activation, pooling, and fully connected. Each layer plays a specific role in ... Aug 16, 2024 ... Reinforcement learning. Actor-Critic method · TensorFlow agents. tf ... This tutorial demonstrates training a simple Convolutional Neural Network ... This paper presents “EspiNet V2” a Deep Learning model, based on the region-based detector Faster R-CNN. The model is used for the detection of motorcycles ...