Real-Time Embedded Traffic Sign Recognition Using Efficient Convolutional Neural Network
IEEE Access, 2019 Traffic sign recognition(TSR) based on deep learning is rapidly developing. Specifically, TSR contains two technologies, namely, traffic sign classification (TSC) and traffic sign detection (TSD). However, the challenge of TSR is to ensure its efficiency,
Xie Bangquan, Weng Xiao Xiong
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A novel text sentiment analysis system using improved depthwise separable convolution neural networks. [PDF]
PeerJ Comput Sci, 2023 Kong X, Zhang K.
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PydMobileNet: Improved Version of MobileNets with Pyramid Depthwise Separable Convolution
CoRR, 2018 Convolutional neural networks (CNNs) have shown remarkable performance in various computer vision tasks in recent years. However, the increasing model size has raised challenges in adopting them in real-time applications as well as mobile and embedded vision applications. Many works try to build networks as small as possible while still have acceptable
Van-Thanh Hoang, Kang-Hyun Jo
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InformationTransmission lines in complex outdoor environments often suffer external damage in construction areas, severely affecting the stability of power systems. Traditional manual detection methods have problems of low efficiency and poor real-time performance.
Min Liu, Benhui Wu, Ming Chen
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Optimising seizure prediction with reduced computational resources using depthwise CNN
Journal of Edge ComputingExisting deep learning models for epileptic seizure prediction are accurate but parameter-heavy, which limits their deployment on wearable and other resource-constrained edge devices.
Ritesh Dhananjay Nikose +1 more
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Multi-scale Xception based depthwise separable convolution for single image super-resolution. [PDF]
PLoS One, 2021 Muhammad W, Aramvith S, Onoye T.
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A Lightweight Dangerous Liquid Detection Method Based on Depthwise Separable Convolution for X-Ray Security Inspection. [PDF]
Comput Intell Neurosci, 2022 Liu D, Liu J, Yuan P, Yu F.
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Real-Time Super Resolution Utilizing Dilation and Depthwise Separable Convolution
Engineering ProceedingsComputer vision applications require high-quality reproductions of original images, typically demanding complex models with many trainable parameters and floating-point operations.
Che-Cheng Chang +4 more
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Joint optic disc and cup segmentation based on densely connected depthwise separable convolution deep network. [PDF]
BMC Med Imaging, 2021 Liu B, Pan D, Song H.
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Maize Leaf Disease Detection Based on an Improved YOLOv11n Model
AlgorithmsTo address the challenges in maize leaf disease detection, including large variation in lesion scales, weak texture of small targets, strong background interference, limited recall ability for blurred lesions, and computational redundancy of conventional
Haifeng Fu +4 more
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