Results 1 to 10 of about 4,746 (266)
A taxonomy of Deep Convolutional Neural Nets for Computer Vision [PDF]
Frontiers in Robotics and AI, 2016 Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features.
Suraj eSrinivas +5 more
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Entangled q-convolutional neural nets
Machine Learning: Science and Technology, 2021 We introduce a machine learning model, the q-CNN model, sharing key features with convolutional neural networks and admitting a tensor network description. As examples, we apply q-CNN to the MNIST and Fashion MNIST classification tasks. We explain how the network associates a quantum state to each classification label, and study the entanglement ...
Vassilis Anagiannis, Miranda C N Cheng
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CAE-CNN-Based DOA Estimation Method for Low-Elevation-Angle Target
Remote Sensing, 2022 For the DOA (direction of arrival) estimation of a low-elevation-angle target under the influence of a multipath effect, this paper proposes a DOA estimation method based on CAE (convolutional autoencoder) and CNN (convolutional neural network).
Fangzheng Zhao +3 more
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CDF‐net: A convolutional neural network fusing frequency domain and spatial domain features
IET Computer Vision, 2023 Convolutional neural network (CNN), as a classic deep learning algorithm, has been applied to various computer vision tasks. However, most classic CNN models focus on the extraction and utilisation of spatial domain features, while ignoring the potential
Aitao Yang +7 more
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Microstrip antenna modelling based on image‐based convolutional neural network
Electronics Letters, 2023 Convolutional neural networks (CNN) have a strong feature extraction ability for images and present a high level of efficiency and accuracy in object detection and image recognition.
Hao Fu +4 more
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Convex Relaxations of Convolutional Neural Nets [PDF]
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019 We propose convex relaxations for convolutional neural nets with one hidden layer where the output weights are fixed. For convex activation functions such as rectified linear units, the relaxations are convex second order cone programs which can be solved very efficiently.
Bartan, Burak, Pilanci, Mert
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Rumour Detection Based on Graph Convolutional Neural Net [PDF]
IEEE Access, 2021 Rumor detection is an important research topic in social networks, and lots of rumor detection models are proposed in recent years. For the rumor detection task, structural information in a conversation can be used to extract effective features. However, many existing rumor detection models focus on local structural features while the global structural
Na Bai +3 more
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A method for superfine pavement crack continuity detection based on topological loss
Electronics Letters, 2023 Deep convolutional neural networks have become a popular tool for the automatic detection of pavement cracks. Despite their widespread use, the models currently available tend to emphasize pixel‐level classification accuracy for cracks, often overlooking
Guohui Jia +4 more
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ROADSIDE FOREST MODELING USING DASHCAM VIDEOS AND CONVOLUTIONAL NEURAL NETS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Tree failure is a primary cause of storm-related power outages throughout the United States. Roadside vegetation management is therefore critical to electric utility companies to prevent power outages during extreme weather conditions. It is difficult to
D. Joshi, C. Witharana
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Human stability assessment and fall detection based on dynamic descriptors
IET Image Processing, 2023 Fall detection systems use a number of different technologies to achieve their goals. This way, they contribute to better life conditions for the elderly community.
Jesús Gutiérrez +2 more
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