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1. An empirical study of feature extraction for Hubei folk art of carved paper-cutting.

Author

Yang, Zhen, Liu, Yanqi, Wang, Weiling, Li, Yu, and Yuan, Xiuxia

Subjects
AESTHETICS, REGIONAL development, CULTURAL values, FEATURE extraction, PAPER arts
Abstract

Excellent traditional culture is the root and soul of a nation, which is the carrier of historical precipitation and continuous development. In this aspect, Hubei folk art of carved paper-cutting has important cultural value and historical significance in the composition of Chinese traditional culture, which is a national intangible cultural heritage under key protection and urgently needs to be carried forward. This paper carried out an empirical study using the survey and comparative analysis methods on the feature extraction for Hubei folk art of carved paper-cutting. Through investigation and comparative analysis of vast artworks of Hubei carved paper-cutting, the classics are selected as the representative to extract the regional characteristics, the artistic values, and the composition and modelling methods. Results indicate that the common features exist on the artistic values in beautification of life and education, the composition principles of central-based, symmetry, balanced or conformal, and the modelling techniques using Yin and Yang carving, unobstructive perspective, distortion and exaggeration. However, the regional features in cultural expression, folklore communication, modelling skills are apparent and strong interlinked with the regional historical development in social activities, labor productivity and surrounding environment. This study provides a multi-dimensional perspective for the modern inheritance and development of traditional Hubei artworks of carved paper-cutting with specified characteristics. [ABSTRACT FROM AUTHOR]

Published
2024
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6. A Multi-layered Approach to Brain Tumor Classification Using VDC-12

Author

Mehta, Anant, Sengupta, Prajit, Rana, Prashant Singh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Aurelia, Sagaya, editor, J., Chandra, editor, Immanuel, Ashok, editor, Mani, Joseph, editor, and Padmanabha, Vijaya, editor

Published
2024
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8. Improving PSO-SVM for Fatigue Recognition

Author

Chai, Pan, Wang, Mei, Chen, Xing, Yang, Yangliu, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Lu, Huimin, editor, and Cai, Jintong, editor

Published
2024
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10. Iris Recognition Network Based on Full Coordinate Attention

Author

Liu, Xina, Xu, Xinying, Zhang, Jiayan, Li, Pengyue, Tang, Jijun, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Sun, Fuchun, editor, Meng, Qinghu, editor, Fu, Zhumu, editor, and Fang, Bin, editor

Published
2024
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11. Broad Learning System Based on Fusion Features

Author

Hu, Dongmei, Xu, Xinying, Xing, Jiwei, Xie, Gang, Tang, Jijun, Li, Rong, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Sun, Fuchun, editor, Meng, Qinghu, editor, Fu, Zhumu, editor, and Fang, Bin, editor

Published
2024
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12. Identification of document paper using hybrid feature extraction.

Author

Lee, Joong, Kim, Hongseok, Yook, Simyub, and Kang, Tae‐Yi

Subjects
CONVOLUTIONAL neural networks, IDENTIFICATION documents, CRIMINAL procedure, FORGERY, FEATURE extraction, PAPER products
Abstract

Document forgery is a significant issue in Korea, with around ten thousand cases reported every year. Analyzing paper plays a crucial role in examining questionable documents such as marketable securities and contracts, which can aid in solving criminal cases of document forgery. Paper analysis can also provide essential insights in other types of criminal cases, serving as an important clue for solving cases such as the source of a blackmail letter. The papermaking process generates distinct forming fabric marks and formations, which are critical features for paper classification. These characteristics are observable under transmitted light and are created by the forming fabric pattern and the distribution of pulp fibers, respectively. In this study, we propose a novel approach for paper identification based on hybrid features. This method combines texture features extracted from images converted using the gray‐level co‐occurrence matrix (GLCM) approach and a convolutional neural network (CNN), with another set of features extracted by the CNN using the same images as input. We applied the proposed method to classification tasks for seven major paper brands available in the Korean market, achieving an accuracy of 97.66%. The results confirm the applicability of this method for visually inspecting paper products and demonstrate its potential for assisting in solving criminal cases involving document forgery. [ABSTRACT FROM AUTHOR]

Published
2023
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14. Speech Emotion Recognition: An Empirical Analysis of Machine Learning Algorithms Across Diverse Data Sets

Author

Ahammed, Mostafiz, Sheikh, Rubel, Hossain, Farah, Liza, Shahrima Mustak, Rahman, Muhammad Arifur, Mahmud, Mufti, Brown, David J., Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Mahmud, Mufti, editor, Ben-Abdallah, Hanene, editor, Kaiser, M. Shamim, editor, Ahmed, Muhammad Raisuddin, editor, and Zhong, Ning, editor

Published
2024
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17. Rose Plant Disease Detection Using Image Processing and Machine Learning

Author

Sharma, Anushka, Dubey, Ghanshyam Prasad, Singh, Ashish, Likhar, Ananya, Mourya, Shailendra, Sharma, Anupam, Nair, Rajit, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Botto-Tobar, Miguel, editor, Zambrano Vizuete, Marcelo, editor, Montes León, Sergio, editor, Torres-Carrión, Pablo, editor, and Durakovic, Benjamin, editor

Published
2024
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22. A Novel Stance Labeling Algorithm for Misinformation Detection

Author

Saini, Jatinderkumar R., Vaidya, Shraddha, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Rajagopal, Sridaran, editor, Popat, Kalpesh, editor, Meva, Divyakant, editor, and Bajeja, Sunil, editor

Published
2024
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23. Machine Learning Algorithms are Used for Fake Review Detection

Author

Asaad, Wesam Hameed, Allami, Ragheed, Ali, Yossra Hussain, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, García Márquez, Fausto Pedro, editor, Jamil, Akhtar, editor, Hameed, Alaa Ali, editor, and Segovia Ramírez, Isaac, editor

Published
2024
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24. Event Categorization from News Articles Using Machine Learning Techniques

Author

Shanmugavadivel, Kogilavani, Subramanian, Malliga, Vasantharan, K., Prethish, G. A., Sankar, S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Chakravarthi, Bharathi Raja, editor, B, Bharathi, editor, García Cumbreras, Miguel Ángel, editor, Jiménez Zafra, Salud María, editor, Subramanian, Malliga, editor, Shanmugavadivel, Kogilavani, editor, and Nakov, Preslav, editor

Published
2024
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26. Classification of Colorectal Cancer Tissue Utilizing Machine Learning Algorithms

Author

Reddy, N. Sai Satwik, Manoj, A. Venkata Siva, Sowmya, V., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Rodrigues, Joel J. P. C., editor, Gupta, Suneet Kumar, editor, Cheng, Xiaochun, editor, Sarao, Pushpender, editor, and Patel, Govind Singh, editor

Published
2024
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27. Video-Based Action Recognition of Spatial and Temporal Deep Learning Models

Author

Jayamohan, M., Yuvaraj, S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Swagatam, editor, Saha, Snehanshu, editor, Coello Coello, Carlos A., editor, and Bansal, Jagdish C., editor

Published
2024
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28. An Investigational Analysis of Automatic Speech Recognition on Deep Neural Networks and Gated Recurrent Unit Model

Author

Soundarya, M., Anusuya, S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Swagatam, editor, Saha, Snehanshu, editor, Coello Coello, Carlos A., editor, and Bansal, Jagdish C., editor

Published
2024
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29. Pattern Recognition Techniques in Image-Based Material Classification of Ancient Manuscripts

Author

Dhali, Maruf A., Reynolds, Thomas, Alizadeh, Aylar Ziad, Nijdam, Stephan H., Schomaker, Lambert, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, De Marsico, Maria, editor, Di Baja, Gabriella Sanniti, editor, and Fred, Ana, editor

Published
2024
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31. Survey on Lidar Sensing Technology for Vehicular Networks

Author

Guinoubi, Mouaouia, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Jemili, Imen, editor, Mosbah, Mohamed, editor, Mabrouk, Sabra, editor, and Mendiboure, Leo, editor

Published
2024
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32. Using Data Mining Techniques to Analyze Facial Expression Motion Vectors

Author

Roshanzamir, Mohamad, Alizadehsani, Roohallah, Roshanzamir, Mahdi, Shoeibi, Afshin, Gorriz, Juan M., Khosravi, Abbas, Nahavandi, Saeid, Acharya, U. Rajendra, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Moosaei, Hossein, editor, Hladík, Milan, editor, and Pardalos, Panos M., editor

Published
2024
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36. Digitization Techniques for the Representation of Genomic Sequences in LSTM-Based Models

Author

Adebiyi, Marion, Enwere, Miracle Nmesomachi, Shekari, Abenego, Adebiyi, Ayodele, Osang, Francis B., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nagar, Atulya K., editor, Singh Jat, Dharm, editor, Mishra, Durgesh Kumar, editor, and Joshi, Amit, editor

Published
2023
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37. Fruit Segregation Using Deep Learning

Author

Dehankar, Archana, Dharmik, Hemanshu, Chambhare, Shravani, Kohad, Darshna, Hingwe, Janvi, Dhoke, Kaustubh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Saini, Mukesh Kumar, editor, Goel, Neeraj, editor, Shekhawat, Hanumant Singh, editor, Mauri, Jaime Lloret, editor, and Singh, Dhananjay, editor

Published
2023
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38. A Comprehensive Study on Feature Extraction Techniques for Indian Sign Language Recognition System

Author

Aziz, Shafaque, Amjad, Mohammad, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Chandran K R, Sarath, editor, N, Sujaudeen, editor, A, Beulah, editor, and Hamead H, Shahul, editor

Published
2023
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40. Eye-Tracking Movements—A Comparative Study

Author

Saini, Sunny, Roy, Anup Kumar, Basu, Saikat, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhattacharyya, Siddhartha, editor, Das, Gautam, editor, De, Sourav, editor, and Mrsic, Leo, editor

Published
2023
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41. Multiclass Classification of Online Reviews Using NLP & Machine Learning for Non-english Language

Author

Sharma, Priyanka, Parwekar, Pritee, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zaynidinov, Hakimjon, editor, Singh, Madhusudan, editor, Tiwary, Uma Shanker, editor, and Singh, Dhananjay, editor

Published
2023
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42. Offline Text-Independent Writer Identification Using Local Black Pattern Histograms

Author

Bahram, Tayeb, Adjoudj, Réda, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Salem, Mohammed, editor, Merelo, Juan Julián, editor, Siarry, Patrick, editor, Bachir Bouiadjra, Rochdi, editor, Debakla, Mohamed, editor, and Debbat, Fatima, editor

Published
2023
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44. A Novel Explainable Deep Learning Model with Class Specific Features

Author

Kuttichira, Deepthi Praveenlal, Azam, Basim, Verma, Brijesh, Rahman, Ashfaqur, Wang, Lipo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yan, Wei Qi, editor, Nguyen, Minh, editor, and Stommel, Martin, editor

Published
2023
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45. The Classification of Native and Invasive Species in North America: A Transfer Learning and Random Forest Pipeline

Author

Sarkar, Sayani, Chakroborty, Somenath, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Santosh, KC, editor, Goyal, Ayush, editor, Aouada, Djamila, editor, Makkar, Aaisha, editor, Chiang, Yao-Yi, editor, and Singh, Satish K, editor

Published
2023
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46. Ash Detection of Coal Slime Flotation Tailings Based on Chromatographic Filter Paper Sampling and Multi-Scale Residual Network.

Author

Wenbo Zhu, Neng Liu, Zhengjun Zhu, Haibing Li, Weijie Fu, Zhongbo Zhang, and Xinghao Zhang

Subjects
COAL ash, FILTER paper, FLOTATION, FEATURE extraction, DEEP learning, FOAM
Abstract

The detection of ash content in coal slime flotation tailings using deep learning can be hindered by various factors such as foam, impurities, and changing lighting conditions that disrupt the collection of tailings images. To address this challenge, we present a method for ash content detection in coal slime flotation tailings. This method utilizes chromatographic filter paper sampling and a multi-scale residual network, which we refer to as MRCN. Initially, tailings are sampled using chromatographic filter paper to obtain static tailings images, effectively isolating interference factors at the flotation site. Subsequently, the MRCN, consisting of a multi-scale residual network, is employed to extract image features and compute ash content. Within the MRCN structure, tailings images undergo convolution operations through two parallel branches that utilize convolution kernels of different sizes, enabling the extraction of image features at various scales and capturing a more comprehensive representation of the ash content information. Furthermore, a channel attention mechanism is integrated to enhance the performance of the model. The combination of the multi-scale residual structure and the channel attention mechanism within MRCN results in robust capabilities for image feature extraction and ash content detection. Comparative experiments demonstrate that this proposed approach, based on chromatographic filter paper sampling and the multi-scale residual network, exhibits significantly superior performance in the detection of ash content in coal slime flotation tailings. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Feature Extraction of Oil–Paper Insulation Raman Spectroscopy Based on Manifold Dimension Transformation

Author

Xingang Chen, Yijie Fan, Zhipeng Ma, Shiyao Tan, Ningyi Li, Xin Song, Yuyang Huang, Jinjing Zhang, and Wenxuan Zhang

Subjects
oil–paper insulation, Raman spectroscopy, feature extraction, state classification, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Transformers play a crucial role in power systems. In this respect, fault diagnosis and aging state assessment have garnered significant attention from researchers. Herein, accelerated thermal aging and Raman scattering experiments are conducted on oil–paper insulation samples to accurately detect aging states. The samples are categorized into different aging stages based on the polymerization degree of the insulating paper. Principal component analysis (PCA), multi-dimensional scale change method (MDS), and isometric mapping algorithm (Isomap) are employed to extract features from the Raman spectra. Subsequently, the XGBoost strong classifier, optimized through Bayesian hyperparameter optimization (BO-XGBoost), is utilized to distinguish between four and ten states among 175 groups of samples after feature extraction. The subsequent classification results of the three feature-extraction methods are compared. The results indicate that Isoamp, which pertains to the manifold dimension transformation, achieves the highest average discriminative accuracy after feature extraction. The discriminative accuracies for aging states four and ten are 97.0% and 95.1% respectively, demonstrating that Raman spectroscopy manifold dimension transformation enhances the distinctiveness between samples of different aging states in the feature-extraction process. The diagnostic model constructed with Isomap and BO-XGBoost enables accurate discrimination of the aging states of oil–paper insulation.

Published
2023
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48. Application of Phonocardiogram and Electrocardiogram Signal Features in Cardiovascular Abnormality Recognition

Author

Ramani, R. Geetha, Ganesh, Abhinand, Balasubramanian, Roshni, Ramkumar, Aruna Srikamakshi, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Fernando, Xavier, editor, and Chandrabose, Aravindan, editor

Published
2023
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