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Depthwise Separable Convolutional Neural Network for Confidential Information Analysis
2020Confidential information analysis can identify the text containing confidential information, thereby protecting organizations from the threat posed by leakage of confidential information. It is effective to build a confidential information analyzer based on a neural network.
Yue Lu +6 more
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Depthwise Separable Convolutional Neural Network for Skin Lesion Classification
2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2019Melanoma is one of the deadliest skin cancers. Early diagnosis plays an essential role in effective treatment planning and reducing the mortality rate of skin cancer. In this study, we propose a compact deep learning-based classification model with a separable convolutional neural network for melanoma detection.
Sara Hosseinzadeh Kassani +4 more
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Automatic Optimising CNN with Depthwise Separable Convolution on FPGA
Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018Convolution layers in Convolutional Neural Networks (CNNs) are effective in vision feature extraction but quite inefficient in computational resource usage. Depthwise separable convolution layer has been proposed in recent publications to enhance the efficiency without reducing the effectiveness by separately computing the spatial and cross-channel ...
Ruizhe Zhao, Xinyu Niu, Wayne Luk
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A Depthwise Separable Convolution Hardware Accelerator for ShuffleNetV2
Convolutional neural networks (CNNs) have been widely applied in the field of computer vision with the development of artificial intelligence. MobileNet and ShuffleNet, among other depthwise separable convolutional neural networks, have gained significant advantages in deploying on resource-constrained embedded devices due to their characteristics suchLinshuang Li, Dihu Chen, Tao Su
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A Reconfigurable Accelerator Design for Quantized Depthwise Separable Convolutions
2021 18th International SoC Design Conference (ISOCC), 2021Yu-Guang Chen +4 more
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CNN With Depthwise Separable Convolutions and Combined Kernels for Rating Prediction
Expert Systems With Applications, 2021Nan Niu, Zahid Younas Khan
exaly
DepthLux: Depthwise Separable Convolution Transformer
2024 International Symposium on Electronics and Telecommunications (ISETC)Raul Balmez, Alexandru Brateanu
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