Article
Computer Science, Artificial Intelligence
Cong Wang, Witold Pedrycz, MengChu Zhou, ZhiWu Li
Summary: The study introduces an improved fuzzy C-means (FCM) model with sparse regularization, which achieves fast and accurate segmentation of real images through MGR operation and feature clustering.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Pranaba K. Mishro, Sanjay Agrawal, Rutuparna Panda, Ajith Abraham
Summary: A novel type-2 adaptive weighted spatial FCM clustering algorithm is proposed for MR brain tissue segmentation. The incorporation of type-2 FCM and spatial information reduces misclassification of noisy pixels and improves the accuracy of cluster center update function. Evaluation using MR image slices demonstrates the superiority and robustness of the algorithm in comparison to state-of-the-art methods.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Shou-Jen Chang-Chien, Yessica Nataliani, Miin-Shen Yang
Summary: Partitional clustering, particularly hard c-means and fuzzy c-means, are popular clustering algorithms but may not perform well in noisy environments or with datasets containing clusters of different shapes. To address these limitations, researchers introduced alternative c-means clustering algorithms AHCM and AFCM, which were further extended to GK-HCM and GK-FCM using Gaussian-kernel clustering. Theoretical analysis and experimental results demonstrate the effectiveness and usefulness of the proposed GK-HCM and GK-FCM algorithms over traditional methods like AHCM and AFCM. These algorithms were also successfully applied to MRI segmentation.
Article
Computer Science, Artificial Intelligence
Qingsen Yan, Shengqiang Liu, Songhua Xu, Caixia Dong, Zongfang Li, Javen Qinfeng Shi, Yanning Zhang, Duwei Dai
Summary: Most recent 3D medical image segmentation methods use CNNs but they cannot explicitly model the long-range dependencies in the medical image. The proposed TransHRNet combines different resolution streams and introduces an Effective Transformer block to learn global information and exchange information across streams. It outperforms other methods on 3D multi-organ segmentation tasks.
PATTERN RECOGNITION
(2023)
Article
Computer Science, Artificial Intelligence
Rong Ma, Wenyi Zeng, Guangcheng Song, Qian Yin, Zeshui Xu
Summary: This paper introduces the Pythagorean fuzzy set (PFS) to handle uncertainty in image segmentation, proposing the Pythagorean fuzzy C-means (PFCM) algorithm. Experimental results on different images and datasets demonstrate the effectiveness and applicability of the proposed algorithm.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Cong Wang, Witold Pedrycz, ZhiWu Li, MengChu Zhou, Shuzhi Sam Ge
Summary: This article elaborates on a similarity-preserving Fuzzy C-Means (FCM) algorithm for G-image segmentation, which introduces a Kullback-Leibler divergence term and considers the spatial information of image pixels to enhance robustness. The proposed FCM is performed in wavelet space for high robustness, demonstrating superior performance compared to state-of-the-art segmentation algorithms while requiring less computation.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Hamza Abdellahoum, Nassim Mokhtari, Abderrahmane Brahimi, Abdelmadjid Boukra
Summary: This paper proposes new approaches to address the issues of selecting cluster numbers and center initialization in the FCM algorithm, utilizing neural networks, Xie and Beni index, histogram, as well as a metaheuristics cooperation method using GA, BBO, and FA. Experimental results show that the proposed methods improve the performance of the basic FCM algorithm and outperform other methods mentioned in the literature.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Weijie Xiao, Yan Zhao, Xiaohui Gao, Congwei Liao, Shengxiang Huang, Lianwen Deng
Summary: A camouflage generation algorithm is proposed in this study to enhance the concealment effect and reduce computing time, while keeping similar domain colors with the background. The algorithm simulates the texture features of the background image through rectangle block segmentation and scrambling, avoiding complex calculations and loss of texture information compared with traditional methods. Fuzzy C-Means (FCM) method is used to accurately extract the main colors of the background image, with experiments showing advantages in reducing computing time and improving simulation effect.
Article
Engineering, Electrical & Electronic
Virna V. Vela-Rincon, Dante Mujica-Vargas, Jose de Jesus Rubio
Summary: This paper explores a method for image segmentation based on hesitant fuzzy set theory, which accelerates processing time with hardware-level parallelization technique and achieves superior segmentation results compared to other methods, preserving region boundary details and homogeneity.
SIGNAL IMAGE AND VIDEO PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Kaixin Zhao, Yaping Dai, Zhiyang Jia, Ye Ji
Summary: The paper proposes a general FCM clustering algorithm based on contraction mapping (cGFCM) for more general cases using Minkowski metric, providing an analytical method for calculating the parameters. The algorithm's core is the construction of a contraction mapping to update prototypes, guided by the Banach contraction mapping principle, with proven correctness and feasibility. Furthermore, experimental studies show that the proposed cGFCM algorithm extends FCM to more general cases with improved performance and reduced running time compared to other clustering methods.
Article
Environmental Sciences
Jingxing Zhu, Feng Wang, Hongjian You
Summary: The existence of multiplicative noise in synthetic aperture radar (SAR) images makes SAR segmentation by fuzzy c-means (FCM) a challenging task. To tackle this problem, we propose two unsupervised FCM segmentation frameworks: LBNL_FCM and GLR_FCM. Both frameworks achieve high segmentation accuracy on simulated and real SAR images.
Article
Computer Science, Information Systems
Wenyi Zeng, Yuqing Liu, Hanshuai Cui, Rong Ma, Zeshui Xu
Summary: This paper presents an image segmentation method based on the interval possibilistic C-means algorithm. By expanding the image pixels to interval values and utilizing secondary feature extraction, the clustering results are improved.
INFORMATION SCIENCES
(2022)
Article
Engineering, Multidisciplinary
Haojie Guo, Dedong Yang
Summary: This paper introduces an improved semantic segmentation model named PRDNet, which utilizes ResNet and dilated convolution to simultaneously extract multi-layer features of medical images. The multi-layer features are fused according to the structure of feature pyramid network in the decoding stage. After experiments on CHAOS and ISIC2017 datasets, the proposed algorithm shows a 1%-4% improvement in different evaluation metrics compared to other algorithms.
Article
Computer Science, Artificial Intelligence
Kaixin Zhao, Yaping Dai, Zhiyang Jia, Ye Ji
Summary: This paper proposes a definition of fuzziness to measure the fuzziness of different versions of FCM and solves the clustering problem of FCM under different distance metrics and fuzzy degrees with the proposed GFCM algorithm. Extensive experiments show that the choice of fuzzy degree has a more significant impact on the performance of FCM-based clustering algorithms.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
C. Jaspin Jeba Sheela, G. Suganthi
Summary: The proposed method utilizes Greedy Snake Model and Fuzzy C-Means optimization for automatic brain tumor segmentation in MRI images, accurately identifying the tumor region through morphological reconstruction and refining the segmentation using the snake model and C-Means algorithm, ultimately selecting the region with a large perimeter to eliminate inaccuracies.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Yun Xie, Peng Li, Nadia Nedjah, Brij B. Gupta, David Taniar, Jindan Zhang
Summary: Edge computing provides a solution to the limited storage and computing resources of IoT-based face recognition systems, but data privacy leak remains a problem. This study proposes a general privacy protection framework, utilizing local differential privacy algorithm and identity authentication technology to protect the privacy of face data.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Shiwen Zhang, Biao Hu, Wei Liang, Kuan-Ching Li, Brij B. Gupta
Summary: This article proposes a caching-based dual K-anonymous (CDKA) location privacy-preserving scheme in edge computing environments. The scheme uses an edge server to protect user location privacy by reducing device load and providing dual anonymity. Through security analysis and performance evaluation, the robustness and relatively low communication cost of the scheme are demonstrated.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Samrah Mehraj, Subreena Mushtaq, Shabir A. Parah, Kaiser J. Giri, Javaid A. Sheikh, Amir H. Gandomi, Mohammad Hijji, Brij B. Gupta, Khan Muhammad
Summary: Heritage multimedia is a valuable cultural asset that provides insights into earlier generations and their creative approach, lifestyle, and historical ideologies. It is also an important resource for boosting the local economy, sustainable communities, and tourism and business sectors. With the advancements in technology and 5G networks, protecting heritage media from unauthorized consumers is crucial. This study proposes a robust and blind watermarking-framework for cultural images (RBWCI) that uses the discrete cosine transform domain for ownership verification and copyright protection.
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Kwok Tai Chui, Brij B. Gupta, Rutvij H. Jhaveri, Hao Ran Chi, Varsha Arya, Ammar Almomani, Ali Nauman
Summary: This paper proposes a multiround transfer learning and modified generative adversarial network (MTL-MGAN) algorithm for lung cancer detection. The algorithm maximizes transferability through a multiround transfer learning process and avoids negative transfer through customized loss functions. The proposed algorithm significantly improves accuracy compared to related works.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Editorial Material
Computer Science, Artificial Intelligence
Lidia Ogiela, Arcangelo Castiglione, Brij B. Gupta, Dharma P. Agrawal
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Qin Zhang, Zhiwei Guo, Yanyan Zhu, Pandi Vijayakumar, Aniello Castiglione, Brij B. Gupta
Summary: This paper proposes a deep learning-based fast fake news detection model for cyber-physical social services. It takes Chinese text as the objective and adopts characters as the basic processing unit. By using a convolution-based neural computing framework, it extracts feature representation for news texts, ensuring both processing speed and detection ability for Chinese short texts. Experimental results show that this model has lower training time cost and higher classification accuracy than baseline methods.
PATTERN RECOGNITION LETTERS
(2023)
Article
Business
Barnali Chaklader, Brij B. Gupta, Prabin Kumar Panigrahi
Summary: The purpose of this research is to provide an overview of the progress of FINTECH companies and their integration with cutting-edge technologies such as AI, machine learning, and blockchain for innovation and entrepreneurship. The study analyzed 302 research papers published in English between 2014 and 2022 using the Scopus database. Qualitative data analysis techniques were used to identify important journals, countries, and authors in the field. The research highlights current trends and suggests new avenues for further exploration.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Business
Fei Zhou, Xue Li, Chunjia Han, Lan Zhang, Brij B. Gupta
Summary: Based on an empirical analysis of 480 valid questionnaires from the Asia-Pacific region, this study found that entrepreneurial support systems have a positive impact on international corporate entrepreneurship (ICE). It also found that resource slack acts as a mediator between institutional support and ICE, and local and ultra-local network embeddedness moderate the relationship between institutional support and resource slack.
INTERNATIONAL ENTREPRENEURSHIP AND MANAGEMENT JOURNAL
(2023)
Article
Business
Brij B. Gupta, Akshat Gaurav, Prabin Kumar Panigrahi
Summary: Smart and innovative education is essential for the development of sustainable entrepreneurship practices and aims to teach young people to be responsible members of society and play an active role in shaping the future. However, traditional teaching techniques are insufficient, and the integration of cutting-edge technologies such as IoT, cloud computing, AI, and machine learning is required to achieve a better future.
INTERNATIONAL ENTREPRENEURSHIP AND MANAGEMENT JOURNAL
(2023)
Article
Business
Shizhen Bai, Hao He, Chunjia Han, Mu Yang, Dingyao Yu, Xinrui Bi, Brij B. B. Gupta, Weijia Fan, Prabin Kumar Panigrahi
Summary: This study examines the impact of thematic influences on theme park visitors' satisfaction using user-generated data. Through the analysis of 112,000 reviews posted by visitors to Shanghai Disney Resort, the study employs structural topic modeling to reveal the dynamics of user-generated data over time. The findings indicate that visitors' satisfaction is closely related to service quality and their overall playing experience, with different emphasis among early and later tourists. Furthermore, the relationship between customer reviews and ratings by tourists becomes less significant over time, suggesting that reviews are better indicators of subjective feelings or experiences. The study contributes to the literature on tourism, service, and consumer behavior, offering practical implications.
JOURNAL OF CONSUMER BEHAVIOUR
(2023)
Article
Engineering, Civil
Brij Bhooshan Gupta, Akshat Gaurav, Enrique Cano Marin, Wadee Alhalabi
Summary: Intelligent Transport Systems (ITS) is an emerging technology that aims to enhance driving experience by enabling communication between smart vehicles and Road-Side Units (RSUs). Researchers are currently focused on detecting malicious nodes and attack traffic in ITS, and have proposed graph-based machine learning techniques for this purpose.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Business
Brij B. Gupta, Akshat Gaurav, Prabin Kumar Panigrahi
Summary: The implementation of a system that facilitates safe and efficient data transmission in the healthcare industry could greatly benefit various aspects of healthcare. However, there are challenges in handling the large quantity of data generated by smart devices in B2B-based healthcare systems.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Computer Science, Information Systems
Xiang Yu, Chonghua Wang, Xiaojing Zheng, Chaoyu Zeng, Brij B. Gupta
Summary: This paper constructs a non-cooperative/cooperative stochastic differential game model to prove that the optimal strategies trajectory of agents in a system with a topological configuration of a Multi-Local-World graph would converge into a certain attractor if the system's configuration is fixed. It is concluded that the optimal strategy trajectory with a nonlinear operator of cooperative/non-cooperative stochastic differential game between agents can make agents in a certain Local-World coordinate and make the Local-World payment maximize, and can make the all Local-Worlds equilibrated; furthermore, the optimal strategy of the coupled game can converge into a particular attractor that decides the optimal property.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Computer Science, Information Systems
Ammar Almomani, Mohammed Alweshah, Waleed Alomoush, Mohammad Alauthman, Aseel Jabai, Anwar Abbass, Ghufran Hamad, Meral Abdalla, Brij B. Gupta
Summary: Voice classification is essential for creating intelligent systems that assist with student exams, criminal identification, and security systems. The research aims to develop a system that can predict and classify gender, age, and accent, resulting in the proposal of a new system called Classifying Voice Gender, Age, and Accent (CVGAA). By incorporating rhythm-based features and using backpropagation and bagging algorithms, the voice recognition system's accuracy is significantly improved, with the Bagging algorithm achieving the highest accuracy of 55.39% in the voice common dataset and 78.94% in speech accent for age classification and accent accuracy.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Engineering, Civil
Brij Bhooshan Gupta, Akshat Gaurav, Ching-Hsien Hsu, Bo Jiao
Summary: The maritime transportation system is responsible for providing safe transportation in the vast area covered by water. IoT devices are used for continuous monitoring of vessel performance and secure data sharing to protect confidential information. Identity-based encryption is used for authentication management in this scheme.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
