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Naoko Nitta, Kazuaki Nakamura and Noboru Babaguchi
While visual appearances play a main role in recognizing the concepts captured in images, additional information can provide complementary information for fine-grained image recognition, where concepts with similar visual appearances such as species of b...
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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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Shuai Dong, Zhihua Yang, Wensheng Li and Kun Zou
Conveyors are used commonly in industrial production lines and automated sorting systems. Many applications require fast, reliable, and dynamic detection and recognition for the objects on conveyors. Aiming at this goal, we design a framework that involv...
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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As there is a lack of public mark samples of Tibetan historical document image characters at present, this paper proposes an unsupervised Tibetan historical document character recognition method based on deep learning (UD-CNN).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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Jianlei Kong, Yang Xiao, Xuebo Jin, Yuanyuan Cai, Chao Ding and Yuting Bai
In the realm of smart agriculture technology?s rapid advancement, the integration of various sensors and Internet of Things (IoT) devices has become prevalent in the agricultural sector. Within this context, the precise identification of pests and diseas...
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Kai Ma, Ming-Jun Nie, Sen Lin, Jianlei Kong, Cheng-Cai Yang and Jinhao Liu
Accurate identification of insect pests is the key to improve crop yield and ensure quality and safety. However, under the influence of environmental conditions, the same kind of pests show obvious differences in intraclass representation, while the diff...
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Weijun Li, Jintong Liu, Yuxiao Gao, Xinyong Zhang and Jianlai Gu
The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is ca...
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Bhishan Bhandari, Geonu Lee and Jungchan Cho
Action recognition is an application that, ideally, requires real-time results. We focus on single-image-based action recognition instead of video-based because of improved speed and lower cost of computation. However, a single image contains limited inf...
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Jinguang Gu, Daiwen Wang, Danyang Hu, Feng Gao and Fangfang Xu
In medical texts, temporal information describes events and changes in status, such as medical visits and discharges. According to the semantic features, it is classified into simple time and complex time. The current research on time recognition usually...
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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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Qiang He, Guowei Chen, Wenchao Song and Pengzhou Zhang
Named entity recognition (NER) is a subfield of natural language processing (NLP) that identifies and classifies entities from plain text, such as people, organizations, locations, and other types. NER is a fundamental task in information extraction, inf...
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Daniela Micucci, Marco Mobilio and Paolo Napoletano
Smartphones, smartwatches, fitness trackers, and ad-hoc wearable devices are being increasingly used to monitor human activities. Data acquired by the hosted sensors are usually processed by machine-learning-based algorithms to classify human activities....
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Xiaodong Cui, Zhuofan He, Yangtao Xue, Keke Tang, Peican Zhu and Jing Han
Underwater Acoustic Target Recognition (UATR) plays a crucial role in underwater detection devices. However, due to the difficulty and high cost of collecting data in the underwater environment, UATR still faces the problem of small datasets. Few-shot le...
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Xin Jin, Cheng Lin, Jiangtao Ji, Wenhao Li, Bo Zhang and Hongbin Suo
The extraction of navigation lines plays a crucial role in the autonomous navigation of agricultural robots. This work offers a method of ridge navigation route extraction, based on deep learning, to address the issues of poor real-time performance and l...
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Shi Li and Xiaoting Chen
The task of joint dialogue act recognition (DAR) and sentiment classification (DSC) aims to predict both the act and sentiment labels of each utterance in a dialogue. Existing methods mainly focus on local or global semantic features of the dialogue from...
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Xiang Zhang, Yuchuan Zhou and Lianying Li
Recognizing vessel navigation patterns plays a vital role in understanding maritime traffic behaviors, managing and planning vessel activities, spotting outliers, and predicting traffic. However, the growth in trajectory data and the complexity of mariti...
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Fengyun Xie, Linglan Wang, Haiyan Zhu and Sanmao Xie
Rolling bearings are the core component of rotating machinery. In order to solve the problem that the distribution of collected rolling bearing data is inconsistent during the operation of bearings under complex working conditions, which results in poor ...
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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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Chuan Yin, Binyu Zhang, Wanzeng Liu, Mingyi Du, Nana Luo, Xi Zhai and Tu Ba
Expansion of the entity attribute information of geographic knowledge graphs is essentially the fusion of the Internet?s encyclopedic knowledge. However, it lacks structured attribute information, and synonymy and polysemy always exist. These reduce the ...
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Tahani Alqurashi
Arabic dialect identification (ADI) has recently drawn considerable interest among researchers in language recognition and natural language processing fields. This study investigated the use of a character-level model that is effectively unrestricted in ...
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