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Lexin Zhang, Kuiheng Chen, Liping Zheng, Xuwei Liao, Feiyu Lu, Yilun Li, Yuzhuo Cui, Yaze Wu, Yihong Song and Shuo Yan
This study introduces a novel high-accuracy fruit fly detection model based on the Transformer structure, specifically aimed at addressing the unique challenges in fruit fly detection such as identification of small targets and accurate localization agai...
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Hao An, Ruotong Ma, Yuhan Yan, Tailai Chen, Yuchen Zhao, Pan Li, Jifeng Li, Xinyue Wang, Dongchen Fan and Chunli Lv
This paper aims to address the increasingly severe security threats in financial systems by proposing a novel financial attack detection model, Finsformer. This model integrates the advanced Transformer architecture with the innovative cluster-attention ...
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Hamed Alshammari, Ahmed El-Sayed and Khaled Elleithy
The effectiveness of existing AI detectors is notably hampered when processing Arabic texts. This study introduces a novel AI text classifier designed specifically for Arabic, tackling the distinct challenges inherent in processing this language. A parti...
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Paolo Fantozzi, Valentina Rotondi, Matteo Rizzolli, Paola Dalla Torre and Maurizio Naldi
Moral features are essential components of TV series, helping the audience to engage with the story, exploring themes beyond sheer entertainment, reflecting current social issues, and leaving a long-lasting impact on the viewers. Their presence shows thr...
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Mihael Gudlin, Miro Hegedic, Matija Golec and Davor Kolar
In the quest for industrial efficiency, human performance within manufacturing systems remains pivotal. Traditional time study methods, reliant on direct observation and manual video analysis, are increasingly inadequate, given technological advancements...
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Xinyi Meng and Daofeng Li
The explosive growth of malware targeting Android devices has resulted in the demand for the acquisition and integration of comprehensive information to enable effective, robust, and user-friendly malware detection. In response to this challenge, this pa...
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Jie Zhang, Fan Li, Xin Zhang, Yue Cheng and Xinhong Hei
As a crucial task for disease diagnosis, existing semi-supervised segmentation approaches process labeled and unlabeled data separately, ignoring the relationships between them, thereby limiting further performance improvements. In this work, we introduc...
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Hang Li, Shengjie Zhao and Hao Deng
The extraction of community-scale green infrastructure (CSGI) poses challenges due to limited training data and the diverse scales of the targets. In this paper, we reannotate a training dataset of CSGI and propose a three-stage transfer learning method ...
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Diana Bratic, Marko ?apina, Denis Jurecic and Jana ?iljak Gr?ic
This paper addresses the challenges associated with the centralized storage of educational materials in the context of a fragmented and disparate database. In response to the increasing demands of modern education, efficient and accessible retrieval of m...
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Ji-Woon Lee and Hyun-Soo Kang
The escalating use of security cameras has resulted in a surge in images requiring analysis, a task hindered by the inefficiency and error-prone nature of manual monitoring. In response, this study delves into the domain of anomaly detection in CCTV secu...
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