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Yadong Li, Rujia Li, Rongbiao Ji, Yehui Wu, Jiaojiao Chen, Mengyao Wu and Jianping Yang
Grain legumes play a significant global role and are integral to agriculture and food production worldwide. Therefore, comprehending and analyzing the factors that influence grain legume yield are of paramount importance for guiding agricultural manageme...
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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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Ying Chen, Xi Qiao, Feng Qin, Hongtao Huang, Bo Liu, Zaiyuan Li, Conghui Liu, Quan Wang, Fanghao Wan, Wanqiang Qian and Yiqi Huang
Invasive plant species pose significant biodiversity and ecosystem threats. Real-time identification of invasive plants is a crucial prerequisite for early and timely prevention. While deep learning has shown promising results in plant recognition, the u...
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Dario Macaluso, Francesco Licciardo and Katya Carbone
In recent years, the primary sector in Italy and elsewhere has been profoundly affected by climate change and a deep economic crisis, mainly linked to stagnating prices and rising production costs. Because of this situation, we are witnessing renewed int...
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Enrico Santangelo, Angelo Del Giudice, Simone Figorilli, Simona Violino, Corrado Costa, Marco Bascietto, Simone Bergonzoli and Claudio Beni
The autonecrotic tomato line V20368 (working code IGSV) spontaneously develops necrotic lesions with acropetal progression in response to an increase in temperature and light irradiation. The process is associated with the interaction between tomato and ...
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Jean-Sébastien Dessureault, Félix Clément, Seydou Ba, François Meunier and Daniel Massicotte
The field of interior home design has witnessed a growing utilization of machine learning. However, the subjective nature of aesthetics poses a significant challenge due to its variability among individuals and cultures. This paper proposes an applied ma...
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Liusheng Han, Xiangyu Wang, Dan Li, Wenjie Yu, Zhaohui Feng, Xingqiang Lu, Shengshuai Wang, Zhiyi Zhang, Xin Gao and Junfu Fan
The lack of high-spectral and high-resolution remote sensing data is impeding the differentiation of various fruit tree species that share comparable spectral and spatial features, especially for evergreen broadleaf trees in tropical and subtropical area...
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Xueliang Wang, Nan Yang, Enjun Liu, Wencheng Gu, Jinglin Zhang, Shuo Zhao, Guijiang Sun and Jian Wang
In order to solve the problem of manual labeling in semi-supervised tree species classification, this paper proposes a pixel-level self-supervised learning model named M-SSL (multisource self-supervised learning), which takes the advantage of the informa...
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Jianjun Chen, Zizhen Chen, Renjie Huang, Haotian You, Xiaowen Han, Tao Yue and Guoqing Zhou
When employing remote sensing images, it is challenging to classify vegetation species and ground objects due to the abundance of wetland vegetation species and the high fragmentation of ground objects. Remote sensing images are classified primarily acco...
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Muhammad Usman, Mahnoor Ejaz, Janet E. Nichol, Muhammad Shahid Farid, Sawaid Abbas and Muhammad Hassan Khan
Farmland trees are a vital part of the local economy as trees are used by farmers for fuelwood as well as food, fodder, medicines, fibre, and building materials. As a result, mapping tree species is important for ecological, socio-economic, and natural r...
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