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Jie Ren, Changmiao Li, Yaohui An, Weichuan Zhang and Changming Sun
Few-shot fine-grained image classification (FSFGIC) methods refer to the classification of images (e.g., birds, flowers, and airplanes) belonging to different subclasses of the same species by a small number of labeled samples. Through feature representa...
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Chenhong Yan, Shefeng Yan, Tianyi Yao, Yang Yu, Guang Pan, Lu Liu, Mou Wang and Jisheng Bai
Ship-radiated noise classification is critical in ocean acoustics. Recently, the feature extraction method combined with time?frequency spectrograms and convolutional neural networks (CNNs) has effectively described the differences between various underw...
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Xiaojuan Wang and Weilan Wang
As there is a lack of public mark samples of Tibetan historical document image characters at present, this paper proposes an unsupervised Tibetan historical document character recognition method based on deep learning (UD-CNN). Firstly, using the Tibetan...
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Jie Huang, Yunpeng Cui and Shuo Wang
Aspect-based sentiment analysis is a fine-grained sentiment analysis task that consists of two types of subtasks: aspect term extraction and aspect sentiment classification. In the aspect term extraction task, current methods suffer from the lack of fine...
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Brendan C. O?Kelly, Jacinto Alonso-Azcárate and José Manuel Moreno-Maroto
The remolding toughness property of fine-grained soil has not been investigated that much, mainly because it has not lent easily to direct measurement, with soil toughness usually qualitatively described. In practical terms, as the plastic limit wP is ap...
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Demiao Yu, Xiaoran Huang, Hengyi Zang, Yuanwei Li, Yuchen Qin and Daoyong Li
The outbreak of COVID-19 in Beijing has been sporadic since the beginning of 2022 and has become increasingly severe since October. In China?s policy of insisting on dynamic clearance, fine-grained management has become the focus of current epidemic prev...
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Hongmei Zhang and Shuiqing Wang
The analysis of thin sections for lithology identification is a staple technique in geology. Although recent strides in deep learning have catalyzed the development of models for thin section recognition leveraging varied deep neural networks, there rema...
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Giorgio Maria Di Nunzio and Riccardo Minzoni
A survey published by Nature in 2016 revealed that more than 70% of researchers failed in their attempt to reproduce another researcher?s experiments, and over 50% failed to reproduce one of their own experiments; a state of affairs that has been termed ...
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Yejin Lee, Suho Lee and Sangheum Hwang
Fine-grained image recognition aims to classify fine subcategories belonging to the same parent category, such as vehicle model or bird species classification. This is an inherently challenging task because a classifier must capture subtle interclass dif...
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Luís Fonseca, Fernando Ribeiro and José Metrôlho
In-bed posture classification has attracted considerable research interest and has significant potential to enhance healthcare applications. Recent works generally use approaches based on pressure maps, machine learning algorithms and focused mainly on f...
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