Results 21 to 30 of about 42,190 (170)
A Helium Speech Unscrambling Algorithm Based on Deep Learning
Information, 2023 Helium speech, the language spoken by divers in the deep sea who breathe a high-pressure helium–oxygen mixture, is almost unintelligible. To accurately unscramble helium speech, a neural network based on deep learning is proposed.
Yonghong Chen, Shibing Zhang
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Convolutional Neural Network (CNN): A comprehensive overview
International Journal of Multidisciplinary Research and Growth Evaluation, 2022 Convolutional neural network (CNN), a class of artificial neural network (ANN) is attracting interests of researchers in all research domain. CNN was invented for computer vision. They have also shown to be useful for semantic parsing, sentence modeling and other natural language processing related tasks. Here in this paper we discuss the basics of CNN
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IET Radar, Sonar & Navigation, 2022 Convolution neural networks (CNNs) represent one of the workhorses of artificial intelligence applications. As a typical artificial intelligence application, a high‐resolution range profile (HRRP) target recognition method based on CNNs has aroused a lot
Qian Xiang +5 more
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Understanding of Convolutional Neural Network (CNN): A Review
International Journal of Robotics and Control Systems, 2023 The application of deep learning technology has increased rapidly in recent years. Technologies in deep learning increasingly emulate natural human abilities, such as knowledge learning, problem-solving, and decision-making. In general, deep learning can carry out self-training without repetitive programming by humans.
Purwono Purwono +5 more
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A-CNN: Annularly Convolutional Neural Networks on Point Clouds [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Analyzing the geometric and semantic properties of 3D point clouds through the deep networks is still challenging due to the irregularity and sparsity of samplings of their geometric structures. This paper presents a new method to define and compute convolution directly on 3D point clouds by the proposed annular convolution.
Artem Komarichev +2 more
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IEEE Access, 2019 Digital signal modulation recognition is meaningful for military application and civilian application. In the non-cooperation communication scenario, digital signal modulation recognition will help people identify communication target and have better ...
Ya Tu, Yun Lin
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Micromachines, 2021 The convolutional neural network (CNN) has been proven to have better performance in hyperspectral image (HSI) classification than traditional methods.
Chenming Li +5 more
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Deep Learning: Basics and Convolutional Neural Networks (CNNs)
, 2023 Abstract Deep learning belongs to the broader family of machine learning methods and currently provides state-of-the-art performance in a variety of fields, including medical applications. Deep learning architectures can be categorized into different groups depending on their components. However, most of them share similar modules and
Vakalopoulou, Maria +4 more
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Chinese Word Sense Disambiguation Based on Word translation and Part of speech
Journal of Harbin University of Science and Technology, 2020 For vocabulary ambiguity problem in Chinese, CNN (Convolution Neural Network) is adopted to determine true meaning of ambiguous vocabulary where word, part of speech and translation around its left and right adjacent words are used.
ZHANG Chunxiang +2 more
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CNN 101: Interactive Visual Learning for Convolutional Neural Networks [PDF]
Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020 The success of deep learning solving previously-thought hard problems has inspired many non-experts to learn and understand this exciting technology. However, it is often challenging for learners to take the first steps due to the complexity of deep learning models.
Zijie J. Wang +7 more
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