Zobrazeno 1 - 10
of 1 619
pro vyhledávání: '"detection and classification"'
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 55, Iss 5, Pp 929-936 (2024)
Purposes Leakage detection in underground pipelines such as prestressed concrete cylinder pipes is a crucial aspect of urban infrastructure management and maintenance. In this study, an innovative magnetic anomaly multi-feature fusion network (MMF) i
Externí odkaz:
https://doaj.org/article/c2ae057c98314a4681ddf0b8e58efccb
Publikováno v:
Tongxin xuebao, Vol 45, Pp 160-175 (2024)
With the continuous increase in the scale and variety of malware, traditional malware analysis methods, which relied on manual feature extraction, become time-consuming and error-prone, rendering them unsuitable. To improve detection efficiency and a
Externí odkaz:
https://doaj.org/article/8c3796462a584fe5a0d5758d8c9dc125
Autor:
Rizki Multajam, Ahmad Faisal Mohamad Ayob, W.S. Mada Sanjaya, Aceng Sambas, Volodymyr Rusyn, Andrii Samila
Publikováno v:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, Vol 14, Iss 3 (2024)
This article explores techniques for the detection and classification of fish as an integral part of underwater environmental monitoring systems. Employing an innovative approach, the study focuses on developing real-time methods for high-precision f
Externí odkaz:
https://doaj.org/article/1359b0ad699440b4a29c6f2923452aea
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2023, Vol. 17, Issue 2, pp. 253-305.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-07-2023-0174
Automatic Classification of Unexploded Ordnance (UXO) Based on Deep Learning Neural Networks (DLNNS)
Publikováno v:
Polish Maritime Research, Vol 31, Iss 1, Pp 77-84 (2024)
This article discusses the use of a deep learning neural network (DLNN) as a tool to improve maritime safety by classifying the potential threat to shipping posed by unexploded ordnance (UXO) objects. Unexploded ordnance poses a huge threat to mariti
Externí odkaz:
https://doaj.org/article/bf33a4f9b15c46baa396eb71505edc48
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)
Abstract Distributed energy generation increases the need for smart grid monitoring, protection, and control. Localization, classification, and fault detection are essential for addressing any problems immediately and resuming the smart grid as soon
Externí odkaz:
https://doaj.org/article/47c6d78eb3ee473ba056ec4631e2e380
Autor:
B Kariyanna, M Sowjanya
Publikováno v:
Smart Agricultural Technology, Vol 8, Iss , Pp 100517- (2024)
As per the FAO, the insect pest causes 30 to 40 percent loss every year across the globe. The identification, classification and management of insect pest is very important to avoid significant loss. Practicing the above process by adopting manual me
Externí odkaz:
https://doaj.org/article/f2a953ea7ce648a093cabe65db7de99e
Publikováno v:
Data in Brief, Vol 55, Iss , Pp 110706- (2024)
Forest ecosystems face increasing wildfire threats, demanding prompt and precise detection methods to ensure efficient fire control. However, real-time forest fire data accessibility and timeliness require improvement. Our study addresses the challen
Externí odkaz:
https://doaj.org/article/4630ce259b104035a0aa2154853f67d0
Autor:
Pakruddin B․, Hemavathy R․
Publikováno v:
Data in Brief, Vol 54, Iss , Pp 110284- (2024)
Pomegranate fruit disease detection and classification based on computer vision remains challenging because of various diseases, building the task of collecting or creating datasets is extremely difficult. The usage of machine learning and deep learn
Externí odkaz:
https://doaj.org/article/d459d65c0fd3490bb8edee02e557b330
Publikováno v:
IEEE Access, Vol 12, Pp 148120-148142 (2024)
In this study, aiming to address the challenges posed by interference from communication systems and jammers, we investigate the application of deep learning (DL) in electronic support measures (ESM) radar systems. Our primary objective is to detect,
Externí odkaz:
https://doaj.org/article/d339b9f41b1646dc8ab0b3a95b3f2631