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EEG Emotion Recognition by Fusion of Multi-Scale Features [PDF]
Brain Sciences, 2023 Electroencephalogram (EEG) signals exhibit low amplitude, complex background noise, randomness, and significant inter-individual differences, which pose challenges in extracting sufficient features and can lead to information loss during the mapping ...
Xiuli Du +4 more
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Single-Image Super-Resolution Neural Network via Hybrid Multi-Scale Features
Mathematics, 2022 In this paper, we propose an end-to-end single-image super-resolution neural network by leveraging hybrid multi-scale features of images. Different from most existing convolutional neural network (CNN) based solutions, our proposed network depends on the
Wenfeng Huang +4 more
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Optical Fiber Vibration Signal Recognition Based on the Fusion of Multi–Scale Features [PDF]
Sensors, 2022 Because of the problem of low recognition accuracy in the recognition of intrusion vibration events by the distributed Sagnac type optical fiber sensing system, this paper combines the traditional optical fiber vibration signal recognition idea and the ...
Xinrong Ma +3 more
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Effective Point Cloud Analysis Using Multi-Scale Features [PDF]
Sensors, 2021 Fully exploring the correlation of local features and their spatial distribution in point clouds is essential for feature modeling. This paper, inspired by convolutional neural networks (CNNs), explores the relationship between local patterns and point ...
Qiang Zheng, Jian Sun
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Remote SensingConvolutional neural network (CNN)-based and Transformer-based methods for hyperspectral image (HSI) classification have rapidly advanced due to their unique characterization capabilities. However, the fixed kernel sizes in convolutional layers limit the
Qian Sun +7 more
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A Multi-Scale Feature Selection Method for Steganalytic Feature GFR [PDF]
IEEE Access, 2020 The Rich Model of the Gabor filter (referred to as the GFR steganalytic feature) can detect JPEG-adaptive steganography objects. However, feature dimensionality that is too high will lead to too much computation and will correspondingly reduce the ...
Xinquan Yu +4 more
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Learning multi-scale features for foreground segmentation [PDF]
Pattern Analysis and Applications, 2019 Foreground segmentation algorithms aim segmenting moving objects from the background in a robust way under various challenging scenarios. Encoder-decoder type deep neural networks that are used in this domain recently perform impressive segmentation results.
Long Ang Lim, Hacer Yalim Keles
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Psoriasis severity classification based on adaptive multi-scale features for multi-severity disease [PDF]
Scientific Reports, 2023 Psoriasis is a skin disease that causes lesions of various sizes across the body and can persist for years with cyclic deterioration and improvement. During treatment, and a multiple-severity disease, with irregular severity within the observation area ...
Cho-I. Moon +3 more
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Stereo Matching Method Based on Multi-Scale and Multi-Level Features Fusion [PDF]
Jisuanji gongcheng, 2021 The stereo matching method based on Convolutional Neural Network(CNN) does not make full use of the feature map information of each level in the image,resulting in the poor feature extraction performance in the ill posed region in the image.This paper ...
WANG Jinhe, CHE Zhilong, ZHANG Nan, MENG Fanyun, SU Cuili, TAN Hao
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Automatic Essay Scoring Method Based on Multi-Scale Features
Applied Sciences, 2023 Essays are a pivotal component of conventional exams; accurately, efficiently, and effectively grading them is a significant challenge for educators. Automated essay scoring (AES) is a complex task that utilizes computer technology to assist teachers in ...
Feng Li +4 more
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