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Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 908-925 (2024)
The accurate detection of small object in optical remote sensing images (ORSIs) presents a significant challenge due to the background interference and the small size of the objects, making them susceptible to misdetection and omission. In this artic
Externí odkaz:
https://doaj.org/article/50457042135246cb920121ff20301762
Publikováno v:
IEEE Access, Vol 12, Pp 93426-93449 (2024)
This paper presents a supervised machine learning approach using eight popular classifiers for fault classification in power transmission lines. The classification of faults, indicated by the behavior of the electrical signals associated with them, p
Externí odkaz:
https://doaj.org/article/cba81acd24874debad6c5790f9dce933
Publikováno v:
IEEE Access, Vol 12, Pp 93531-93545 (2024)
Since ancient times, traditional medical analysis has recorded the wrist pulse as an indication of physical health using the perception of three fingertips classified based on their unique characteristics. The analysis outcomes differ from physicians
Externí odkaz:
https://doaj.org/article/2a66fdcea5eb422cbf19db58502d649d
Publikováno v:
IEEE Access, Vol 12, Pp 93363-93371 (2024)
To solve the problem of insufficient melt pool width feature extraction accuracy caused by splash, arc light, and other interferences in the metal deposition process, a melt pool width extraction method based on the variable step size erosion model i
Externí odkaz:
https://doaj.org/article/0093697157c84fa397909ee1d90b46a2
Publikováno v:
IEEE Access, Vol 12, Pp 90768-90781 (2024)
Dynamic texture classification has been widely studied because of its applications in various computer vision tasks. The key to classifying dynamic textures lies in describing them, i.e., extracting features from them. A variety of traditional dynami
Externí odkaz:
https://doaj.org/article/6b292b00806c4f86bbf9f17585e57369
Publikováno v:
IEEE Access, Vol 12, Pp 88939-88949 (2024)
The deterioration of power generation facilities built during the early stages of plant operation is becoming increasingly severe, raising concerns about potential socioeconomic harm from pipe leaks. Consequently, there is a pressing need for rapid l
Externí odkaz:
https://doaj.org/article/13565a3297e7493a9b0c2723e9ad746f
Publikováno v:
IEEE Access, Vol 12, Pp 88715-88727 (2024)
This work introduces Orthogonal Lattice Universal Wavelet Unit, a novel trainable wavelet unit to enhance image classification and anomaly detection in convolutional neural networks by reducing information loss during pooling. The unit employs an ort
Externí odkaz:
https://doaj.org/article/b03ca44add434867a0f2c06612e8f0cb
Publikováno v:
IEEE Access, Vol 12, Pp 87691-87700 (2024)
Identifying lung sound signal patterns is essential for detecting and monitoring respiratory diseases. Existing approaches for analyzing respiratory sounds need domain specialists. Therefore, an accurate and automated lung sound classification tool i
Externí odkaz:
https://doaj.org/article/773a39a95969487780343ad7833d62be
Autor:
Ahmad Sahban Rafsanjani, Norshaliza Binti Kamaruddin, Mehran Behjati, Saad Aslam, Aaliya Sarfaraz, Angela Amphawan
Publikováno v:
IEEE Access, Vol 12, Pp 85001-85026 (2024)
Malicious Uniform Resource Locators (URLs) pose a significant cybersecurity threat by carrying out attacks such as phishing and malware propagation. Conventional malicious URL detection methods, relying on blacklists and heuristics, often struggle to
Externí odkaz:
https://doaj.org/article/a5c3af432cfe46fcac71be94eeaf089e
Publikováno v:
IEEE Access, Vol 12, Pp 84923-84951 (2024)
Early detection of water leakages is crucial due to their social, environmental, and economic impacts. In this regard, machine learning (ML) algorithms have been proposed in the literature to automatically detect leakages using vibration, pressure, a
Externí odkaz:
https://doaj.org/article/72bb5504ba834438ae4f7cab5d7e4808