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Rito Clifford Maswanganyi, Chungling Tu, Pius Adewale Owolawi and Shengzhi Du
Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session ...
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Torrey Wagner, Dennis Guhl and Brent Langhals
Given the emergence of China as a political and economic power in the 21st century, there is increased interest in analyzing Chinese news articles to better understand developing trends in China. Because of the volume of the material, automating the cate...
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Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes and Laurent Risser
Automatic recommendation systems based on deep neural networks have become extremely popular during the last decade. Some of these systems can, however, be used in applications that are ranked as High Risk by the European Commission in the AI act?for ins...
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Muhammad Asad Arshed, Shahzad Mumtaz, Muhammad Ibrahim, Saeed Ahmed, Muhammad Tahir and Muhammad Shafi
Skin cancer, particularly melanoma, has been recognized as one of the most lethal forms of cancer. Detecting and diagnosing skin lesions accurately can be challenging due to the striking similarities between the various types of skin lesions, such as mel...
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Bernardo Panichi and Alessandro Lazzeri
This paper addresses the time-intensive task of assigning accurate account labels to invoice entries within corporate bookkeeping. Despite the advent of electronic invoicing, many software solutions still rely on rule-based approaches that fail to addres...
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Junwei Lang, Zhenjia Zeng, Tengfei Ma and Sailing He
Sudden air pollution accidents (explosions, fires, leaks, etc.) in chemical industry parks may result in great harm to people?s lives, property, and the ecological environment. A gas tracking network can monitor hazardous gas diffusion using traceability...
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Mustafa Pamuk and Matthias Schumann
Corporate credit ratings provide multiple strategic, financial, and managerial benefits for decision-makers. Therefore, it is essential to have accurate and up-to-date ratings to continuously monitor companies? financial situations when making financial ...
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Shuiyan Li, Rongzhi Qi and Shengnan Zhang
Compared with English named entity recognition (NER), Chinese NER faces significant challenges due to the flexible, non-standard word formation and vague word boundaries, which cause a lot of boundary ambiguity and reduce the accuracy of entity identific...
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Mantas Bacevicius and Agne Paulauskaite-Taraseviciene
Various machine learning algorithms have been applied to network intrusion classification problems, including both binary and multi-class classifications. Despite the existence of numerous studies involving unbalanced network intrusion datasets, such as ...
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Hezam Albaqami, Ghulam Mubashar Hassan and Amitava Datta
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Yefang Sun, Jun Gong and Yueyi Zhang
Data imbalance is a common problem in classification tasks. The Mahalanobis-Taguchi system (MTS) has proven to be promising due to its lack of requirements for data distribution. The MTS is a binary classifier. However, multi-classification problems are ...
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Seungkyu Ryu and Minki Kim
In comparison to conventional human-driven vehicles (HVs), connected and automated vehicles (CAVs) provide benefits (e.g., reducing travel time and improving safety). However, before the period of fully CAVs appears, there will be a situation in which bo...
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Gopal Nath, Yawei Wang, Austin Coursey, Krishna K. Saha, Srikanth Prabhu and Saptarshi Sengupta
Productivity losses caused by absenteeism at work cost U.S. employers billions of dollars each year. In addition, employers typically spend a considerable amount of time managing employees who perform poorly. By using predictive analytics and machine lea...
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Aolun Li, Long Yu and Shengwei Tian
Due to the influence of underwater visual characteristics on the observation of underwater creatures, the traditional object detection algorithm is ineffective. In order to improve the robustness of underwater biological detection, based on the YOLOv4 de...
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Juan Chen, Qinxuan Feng and Qi Guo
In order to solve the problem of traffic congestion and emission optimization of urban multi-class expressways, a robust dynamic nondominated sorting multi-objective genetic algorithm DFCM-RDNSGA-III based on density fuzzy c-means clustering method is pr...
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Arunabha M. Roy and Jayabrata Bhaduri
In this paper, a deep learning enabled object detection model for multi-class plant disease has been proposed based on a state-of-the-art computer vision algorithm. While most existing models are limited to disease detection on a large scale, the current...
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Jinfu Liu, Mingliang Bai, Na Jiang, Ran Cheng, Xianling Li, Yifang Wang and Daren Yu
Multi-classifiers are widely applied in many practical problems. But the features that can significantly discriminate a certain class from others are often deleted in the feature selection process of multi-classifiers, which seriously decreases the gener...
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Retno Kusumaningrum, Titan A. Indihatmoko, Saesarinda R. Juwita, Alfi F. Hanifah, Khadijah Khadijah and Bayu Surarso
Stunting is a condition in which children experience impaired growth and development, caused by malnutrition, repeated infections, and inadequate psychosocial stimulation. It often remains unrecognized due to a lack of awareness in the community. Therefo...
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Ali Walid Daher, Ali Rizik, Andrea Randazzo, Emanuele Tavanti, Hussein Chible, Marco Muselli and Daniele D. Caviglia
Nowadays, cities can be perceived as increasingly dangerous places. Usually, CCTV is one of the main technologies used in a modern security system. However, poor light situations or bad weather conditions (rain, fog, etc.) limit the detection capabilitie...
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Antoni Burguera and Francisco Bonin-Font
This paper proposes a method to perform on-line multi-class segmentation of Side-Scan Sonar acoustic images, thus being able to build a semantic map of the sea bottom usable to search loop candidates in a SLAM context. The proposal follows three main ste...
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