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Article
Computer Science, Information Systems
Shuai Liu et al.
Summary: Computer vision, particularly visual monitoring technology, has shown great potential in the complex monitoring environment. This article proposes a fuzzy inference-based monitoring method that utilizes human inertial thinking characteristics to infer the target's location and applies an alternative selection strategy based on thinking set. Experimental results on multiple datasets demonstrate the effectiveness and robustness of the proposed method in IoT-assisted monitoring.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Shuai Liu et al.
Summary: Deep learning has transformed computer vision and is widely used for monitoring in various visual scenes. However, traditional machine-learning methods still have certain advantages in terms of complexity and explainability. Traditional visual tracking approaches, particularly those using correlation filtering, have become popular for understanding complex visual scenes, but they may not fully capture the changing target appearances in dynamic visual scenes, leading to inaccurate target locations.
INFORMATION FUSION
(2023)
Article
Computer Science, Hardware & Architecture
Shuai Liu et al.
Summary: This article introduces a reliable sample selection strategy for weakly supervised visual tracking and verifies its importance in improving model performance. Experiments demonstrate that a scientific sample quality assessment method is of great help to data-based weakly supervised learning systems.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Computer Science, Artificial Intelligence
Shui-Hua Wang et al.
Summary: The study aims to develop an AI tool for diagnosing COVID-19 on chest CT images, and the proposed FGCNet model outperforms 15 state-of-the-art methods, showing its effectiveness in assisting radiologists in detecting COVID-19 rapidly.
INFORMATION FUSION
(2021)
Article
Green & Sustainable Science & Technology
Mahender Singh Kaswan et al.
Summary: This study investigates the barriers to implementing life cycle assessment (LCA) in the manufacturing sector of India using Grey Relational Analysis (GRA) and Best Worst Method (BWM). The findings highlight key obstacles such as lack of top management support, inadequate education and training of employees on environmental management, and insufficient cooperation among supply chain partners. Addressing these barriers is crucial for improving organizational sustainability through the application of LCA.
INTERNATIONAL JOURNAL OF SUSTAINABLE ENGINEERING
(2021)
Article
Agriculture, Multidisciplinary
Usman Ahmed et al.
Summary: In agricultural production, the stable application of nutrients and the use of genetic algorithms can increase crop fertility and yield. By analyzing crop fertility and yield, predicting suitable nutrients for different crops, and providing nutrient recommendations. The final nutrient recommendation is made by comparing recommended patterns with real-time sensor data.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Energy & Fuels
Satheeshkumar Palanisamy et al.
Summary: The study and exploration of massive multiple-input multiple-output (MMIMO) and millimeter-wave wireless access technology has been driven by the shortage of bandwidth in the wireless communication sector. The new concept of the MIMO tri-band hexagonal antenna array enables efficient spectrum and energy efficiency in multiple frequency bands.
Article
Computer Science, Artificial Intelligence
Shuihua Wang et al.
Summary: The advancement of biomedical imaging technologies leads to the daily generation of massive amounts of data, prompting the development of data fusion methods for better understanding. Apart from data generation, factors like noise, missing data, data scarcity, and high dimensionality also need to be considered in the fusion process.
INFORMATION FUSION
(2021)
Article
Food Science & Technology
Lindsay M. Jaacks et al.
Summary: The COVID-19 lockdown in India has primarily impacted farmers' ability to sell their crops and livestock products, leading to decreased daily wages and dietary diversity.
Article
Computer Science, Artificial Intelligence
Bagesh Kumar et al.
Summary: In this paper, a fast training method for OCSSVM is proposed, which enhances its scalability without compromising precision significantly. Experimental results show that the proposed method achieves the best tradeoff between training time and accuracy, providing similar accuracies to regular OCSSVM and better scalability compared to existing state-of-the-art one-class classifiers.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Wojciech Dudzik et al.
Summary: This paper addresses the optimization problem of SVMs for binary classification of difficult datasets, introducing an evolutionary technique and a co-evolutionary scheme. Experimental results show that the proposed algorithm outperforms popular supervised learners and other techniques for optimizing SVMs.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
A. H. Bademlioglu et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2020)
Article
Engineering, Electrical & Electronic
Pradip Kumar Barik et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Computer Science, Artificial Intelligence
Yu-Dong Zhang et al.
INFORMATION FUSION
(2020)
Article
Computer Science, Information Systems
Nir Weinberger et al.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2020)
Article
Computer Science, Information Systems
Dabin Zhang et al.
