What are the advantages and disadvantages of using CNNs versus RNNs for sequence data?

Feb 1, 2023 ... Convolutional Neural Networks (CNNs) is a powerful deep learning architecture well-suited to image classification and object recognition tasks. Explore CNNs in self-driving cars, including reinforcement learning and Partially Observable Markov Decision Processes. Nov 28, 2022 ... In this study, different deep CNN models with multiple machine learning classifiers are investigated for monkeypox disease diagnosis using ... Aug 1, 2019 ... ... CNN), which is kind of deep learning. Mask R-CNN technique is a recently proposed algorithm not only for object detection and object ... 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. Feb 1, 2023 ... A new bio-inspired deep learning model that enables generalization in dynamic lighting conditions. CNN is one of the popular deep learning algorithms that recently gained popularity in the sector of hydrology and earth sciences (Panahi et al., 2020). The CNN ... 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. Feb 23, 2023 ... The CNN and recurrent including LSTM and GRU are all supported on GPU using the native Deep Learning package. The objective of this paper is using deep learning to uncover higher-level representational features, to clearly explain transfer learning, to provide current ...