Results 1 to 10 of about 11,603,043 (210)
Chinese Sentiment Analysis Based on CNN-BiLSTM Model of Multi-level and Multi-scale Feature Extraction [PDF]
Jisuanji kexue, 2023 Sentiment analysis,as a sub-field of natural language processing(NLP),plays a very important role in public opinion monitoring.In the Chinese sentiment analysis task,the existing methods only consider sentiment features from single-level and single-scale,
WANG Lin, MENG Zuqiang, YANG Lina
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A multi-scale features-based method to detect Oplegnathus
Information Processing in Agriculture, 2021 It is of great significance to use underwater video and image processing technology to detect and analyze fish behaviors. In this paper, an Oplegnathus image dataset for fish behaviors study by deep learning algorithm is constructed, and the data is ...
Jun Yue +6 more
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EEG Emotion Recognition by Fusion of Multi-Scale Features
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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Efficient Lightweight Attention Network for Face Recognition
IEEE Access, 2022 Although face recognition has achieved great success due to deep learning, many factors may affect the quality of faces in the wild, such as pose changes, age variations, and light changes, which can seriously affect the performance of face recognition ...
Peng Zhang +3 more
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Double Attention for Multi-Label Image Classification
IEEE Access, 2020 Multi-label image classification is an essential task in image processing. How to improve the correlation between labels by learning multi-scale features from images is a very challenging problem.
Haiying Zhao +3 more
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IEEE Access, 2021 The width of convolutional neural networks (CNNs) is crucial for improving performance. Many wide CNNs use a convolutional layer to fuse multiscale features or fuse the preceding features to subsequent features.
Xiaohong Yu +4 more
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DWANet: Focus on Foreground Features for More Accurate Location
IEEE Access, 2022 Object detection can locate objects in an image using bounding boxes, which can facilitate classification and image understanding, resulting in a wide range of applications.
Jiwei Hu +3 more
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Multi-Time-Scale Features for Accurate Respiratory Sound Classification
Applied Sciences, 2020 The COVID-19 pandemic has amplified the urgency of the developments in computer-assisted medicine and, in particular, the need for automated tools supporting the clinical diagnosis and assessment of respiratory symptoms.
Alfonso Monaco +5 more
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Shape Matching Based on Multi-Scale Invariant Features
IEEE Access, 2019 Shape matching has been extensively used in various fields. The local feature-based or global feature-based algorithms can hardly describe the shape comprehensively due to their inherent defects.
Zhang Kun, Ma Xiao, Li Xinguo
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A Multi-Scale Feature Selection Method for Steganalytic Feature GFR
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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