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Tingkai Hu, Zuqin Chen, Jike Ge, Zhaoxu Yang and Jichao Xu
Insufficiently labeled samples and low-generalization performance have become significant natural language processing problems, drawing significant concern for few-shot text classification (FSTC). Advances in prompt learning have significantly improved t...
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Dezhi Cao, Yue Zhao and Licheng Wu
The construction of pronunciation dictionaries relies on high-quality and extensive training data in data-driven way. However, the manual annotation of corpus for this purpose is both costly and time consuming, especially for low-resource languages that ...
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Yisha Wang, Gang Yang and Hao Lu
Rapid and accurate tree-crown detection is significant to forestry management and precision forestry. In the past few decades, the development and maturity of remote sensing technology has created more convenience for tree-crown detection and planting ma...
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Dominik Stallmann and Barbara Hammer
Novel neural network models that can handle complex tasks with fewer examples than before are being developed for a wide range of applications. In some fields, even the creation of a few labels is a laborious task and impractical, especially for data tha...
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Kokoy Siti Komariah, Ariana Tulus Purnomo, Ardianto Satriawan, Muhammad Ogin Hasanuddin, Casi Setianingsih and Bong-Kee Sin
To pursue a healthy lifestyle, people are increasingly concerned about their food ingredients. Recently, it has become a common practice to use an online recipe to select the ingredients that match an individual?s meal plan and healthy diet preference. T...
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Yongjian Li, He Li, Dazhao Fan, Zhixin Li and Song Ji
Sea ice extraction and segmentation of remote sensing images is the basis for sea ice monitoring. Traditional image segmentation methods rely on manual sampling and require complex feature extraction. Deep-learning-based semantic segmentation methods hav...
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Wenbin Zheng, Jinjin Li and Shujiao Liao
Multi-label learning has become a hot topic in recent years, attracting scholars? attention, including applying the rough set model in multi-label learning. Exciting works that apply the rough set model into multi-label learning usually adapt the rough s...
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Sergey A. Soldatov, Danil M. Pashkov, Sergey A. Guda, Nikolay S. Karnaukhov, Alexander A. Guda and Alexander V. Soldatov
Microscopic tissue analysis is the key diagnostic method needed for disease identification and choosing the best treatment regimen. According to the Global Cancer Observatory, approximately two million people are diagnosed with colorectal cancer each yea...
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Yunya Gao, Stefan Lang, Dirk Tiede, Getachew Workineh Gella and Lorenz Wendt
Refugee-dwelling footprints derived from satellite imagery are beneficial for humanitarian operations. Recently, deep learning approaches have attracted much attention in this domain. However, most refugees are hosted by low- and middle-income countries ...
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Jaekyung Kim, Jungwoo Huh, Ingu Park, Junhyeong Bak, Donggeon Kim and Sanghoon Lee
Deep learning-based object detection is one of the most popular research topics. However, in cases where large-scale datasets are unavailable, the training of detection models remains challenging due to the data-driven characteristics of deep learning. S...
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