Zobrazeno 1 - 10
of 33
pro vyhledávání: '"YanFeng Shang"'
Publikováno v:
Sustainability; Volume 15; Issue 12; Pages: 9164
To address the issues of low automation, reliance on manual screening by professionals, and long detection cycles in current urban drainage pipeline defect detection, this study proposes an improved object detection algorithm called EFE-SSD (enhanced
Autor:
Zhengyan Ding, Yanfeng Shang
Publikováno v:
Communications in Computer and Information Science ISBN: 9789819908554
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::262a67fb3515034ed05f2260ef871061
https://doi.org/10.1007/978-981-99-0856-1_2
https://doi.org/10.1007/978-981-99-0856-1_2
Publikováno v:
Journal of refractive surgery (Thorofare, N.J. : 1995). 37(1)
PURPOSE: To investigate the pathogenicity and immunogenicity of human corneal stromal lenticules from small incision lenticule extraction (SMILE). METHODS: Serological testing was completed prior to sample collection to rule out infectious diseases.
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811525674
This paper proposes a simple and stable point feature-based registration method for synthetic aperture radar (SAR) and optical remote sensing images. First, we extend Harris detector’s response function from linear item to quadratic form and build
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a49de60afddf07a5a8365098b624fd3
https://doi.org/10.1007/978-981-15-2568-1_274
https://doi.org/10.1007/978-981-15-2568-1_274
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030251277
Deep convolutional network has achieved great success in visual recognition of static images, while it is not so advantageous as traditional methods in action recognition in videos. However, in recent years, researchers have proposed a series of huma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f54643972e01cc957a1e49724bfb8565
https://doi.org/10.1007/978-3-030-25128-4_198
https://doi.org/10.1007/978-3-030-25128-4_198
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030251277
Video surveillance applications involve video content modeling, video understanding, video retrieval service and data management, which rely on the exploration of video surveillance knowledge base. In this study, we explore a modeling platform for vi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a035b97d21a9014a687233deb001c68f
https://doi.org/10.1007/978-3-030-25128-4_197
https://doi.org/10.1007/978-3-030-25128-4_197
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030251277
Application orchestration technology has always been one of the research directions of Devops. The traditional application orchestration technology has some problems such as slow deployment and scaling speed. Therefore, this paper proposes a Docker-b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cd7dddc37461156a204687f0f550566
https://doi.org/10.1007/978-3-030-25128-4_199
https://doi.org/10.1007/978-3-030-25128-4_199
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 9:3478-3488
In this paper, a novel change detection method based on conditional random field (CRF) with region connection constraints in multitemporal high-resolution remote sensing images is proposed. The change detection problem is formulated as a labeling iss
Publikováno v:
Physics in Medicine and Biology. 61(No. 6):2283-2301
Portable chest radiographs (CXRs) are commonly used in the intensive care unit (ICU) to detect subtle pathological changes. However, exposure settings or patient and apparatus positioning deteriorate image quality in the ICU. Chest x-rays of patients
Publikováno v:
Computer Vision and Image Understanding. 199:103030
Most prevailing object detection methods share networks and features between localization and classification components, which easily leads to sub-optimal learning for the two separate tasks. In this paper, we propose a conception of task differentia