Results 31 to 40 of about 1,451,519 (348)
Airborne Network Traffic Identification Method under Small Training Samples
Xibei Gongye Daxue Xuebao, 2020 Due to the high cost and difficulty of traffic data set acquisition and the high time sensitivity of traffic distribution, the machine learning-based traffic identification method is difficult to be applied in airborne network environment. Aiming at this
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Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network [PDF]
IEEE Transactions on Medical Imaging, 2017 Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative ...
Hu Chen +7 more
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Switching Convolutional Neural Network for Crowd Counting [PDF]
Computer Vision and Pattern Recognition, 2017 We propose a novel crowd counting model that maps a given crowd scene to its density. Crowd analysis is compounded by myriad of factors like inter-occlusion between people due to extreme crowding, high similarity of appearance between people and ...
Deepak Babu Sam +2 more
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An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Sensors, 2023 Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo +6 more
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Relation-Shape Convolutional Neural Network for Point Cloud Analysis [PDF]
Computer Vision and Pattern Recognition, 2019 Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural Network, which extends regular grid CNN to irregular configuration ...
Yongcheng Liu +3 more
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Content-aware convolutional neural networks [PDF]
Neural Networks, 2021 Accepted by Neural ...
Mingkui Tan +7 more
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Optimization design of binary VGG convolutional neural network accelerator
Dianzi Jishu Yingyong, 2021 Most of the existing researches on accelerators of binary convolutional neural networks based on FPGA are aimed at small-scale image input, while the applications mainly take large-scale convolutional neural networks such as YOLO and VGG as backbone ...
Zhang Xuxin +3 more
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Simplicial Convolutional Neural Networks
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 Graphs can model networked data by representing them as nodes and their pairwise relationships as edges. Recently, signal processing and neural networks have been extended to process and learn from data on graphs, with achievements in tasks like graph signal reconstruction, graph or node classifications, and link prediction.
Yang, M. (author) +2 more
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Diagnostics, 2022 Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning ...
Josefin Sandström +4 more
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A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection [PDF]
European Conference on Computer Vision, 2016 A unified deep neural network, denoted the multi-scale CNN (MS-CNN), is proposed for fast multi-scale object detection. The MS-CNN consists of a proposal sub-network and a detection sub-network.
Zhaowei Cai +3 more
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