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Maryan Rizinski, Andrej Jankov, Vignesh Sankaradas, Eugene Pinsky, Igor Mishkovski and Dimitar Trajanov
The task of company classification is traditionally performed using established standards, such as the Global Industry Classification Standard (GICS). However, these approaches heavily rely on laborious manual efforts by domain experts, resulting in slow...
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William Villegas-Ch, Angel Jaramillo-Alcázar and Sergio Luján-Mora
This study evaluated the generation of adversarial examples and the subsequent robustness of an image classification model. The attacks were performed using the Fast Gradient Sign method, the Projected Gradient Descent method, and the Carlini and Wagner ...
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Haiping Si, Mingchun Li, Weixia Li, Guipei Zhang, Ming Wang, Feitao Li and Yanling Li
Apples, as the fourth-largest globally produced fruit, play a crucial role in modern agriculture. However, accurately identifying apple diseases remains a significant challenge as failure in this regard leads to economic losses and poses threats to food ...
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Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
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Jingyuan Liang, Shuiqing Lin and Xizheng Ke
Four-level pulse amplitude modulation (PAM4) can transmit more information in the same symbol interval, effectively improving the information transmission rate and frequency band utilization of visible light communication (VLC). This paper proposes a met...
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Frank Klawonn and Georg Hoffmann
Clustering algorithms are usually iterative procedures. In particular, when the clustering algorithm aims to optimise an objective function like in k-means clustering or Gaussian mixture models, iterative heuristics are required due to the high non-linea...
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Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)...
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Yoga Sasmita, Heri Kuswanto and Dedy Dwi Prastyo
Standard time-series modeling requires the stability of model parameters over time. The instability of model parameters is often caused by structural breaks, leading to the formation of nonlinear models. A state-dependent model (SDM) is a more general an...
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Lingqi Kong and Shengquau Liu
With the development of the Internet, vast amounts of text information are being generated constantly. Methods for extracting the valuable parts from this information have become an important research field. Relation extraction aims to identify entities ...
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Xiaonan Si, Lei Wang, Wenchang Xu, Biao Wang and Wenbo Cheng
Gout is one of the most painful diseases in the world. Accurate classification of gout is crucial for diagnosis and treatment which can potentially save lives. However, the current methods for classifying gout periods have demonstrated poor performance a...
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