Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Menglong Yang"'
Publikováno v:
IEEE Access, Vol 12, Pp 89479-89492 (2024)
As artificial intelligence (AI) technology advances rapidly, its increasing involvement in military defense fosters intelligent air combat domain development. The Intelligent Flight Controller (IFC) is a crucial technology and foundation for intellig
Externí odkaz:
https://doaj.org/article/74141a85a7104c6c8379e5eda17b2718
Publikováno v:
Sensors, Vol 24, Iss 11, p 3456 (2024)
Few-shot object detection is a challenging task aimed at recognizing novel classes and localizing with limited labeled data. Although substantial achievements have been obtained, existing methods mostly struggle with forgetting and lack stability acr
Externí odkaz:
https://doaj.org/article/c9343b1958e84c1ea6d5a74866a52874
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract Current computer vision tasks based on deep learning require a huge amount of data with annotations for model training or testing, especially in some dense estimation tasks, such as optical flow segmentation and depth estimation. In practice
Externí odkaz:
https://doaj.org/article/8e8ed24e09774e1da0478b9dcafbf963
Publikováno v:
IEEE Access, Vol 9, Pp 36819-36826 (2021)
Cost function is one of the most important topics in face recognition. Classic methods based on anchor-positive-negative sample pairs directly or indirectly have been proved to be effective. Taking advantage of information from sample pair with label
Externí odkaz:
https://doaj.org/article/249184cf355941df8f1dabf60b8bab19
Publikováno v:
IEEE Access, Vol 8, Pp 191530-191541 (2020)
Recently, unsupervised monocular training methods based on convolutional neural networks have already shown surprisingly progress in improving the accuracy of depth estimation. However, the performance of these methods suffers deeply from problematic
Externí odkaz:
https://doaj.org/article/f6e9d230a68945afbc5ec1f0466cf1db
Publikováno v:
Frontiers in Environmental Science, Vol 9 (2021)
This paper investigates whether the macroeconomic uncertainty factors can explain and forecast China’s INE crude oil futures market volatility. We use the GARCH-MIDAS model to investigate the explaining and predicting power of the macroeconomic unc
Externí odkaz:
https://doaj.org/article/ef52c75c4dd14f9db642402fce380d79
Geopolitical Risk and Stock Market Volatility in Emerging Economies: Evidence from GARCH-MIDAS Model
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2021 (2021)
Previous studies have found that geopolitical risk (GPR) caused by geopolitical events such as terrorist attacks can affect the movements of asset prices. However, the studies on whether and how these influences can explain and predict the volatility
Externí odkaz:
https://doaj.org/article/c00b8b0c39b24266951ea2a175d5c7b4
Publikováno v:
Remote Sensing, Vol 13, Iss 7, p 1236 (2021)
Convolutional neural networks (CNNs) have been widely used in change detection of synthetic aperture radar (SAR) images and have been proven to have better precision than traditional methods. A two-stage patch-based deep learning method with a label
Externí odkaz:
https://doaj.org/article/ead2540443be424eb8f3de9599167d98
Publikováno v:
Journal of Applied Mathematics, Vol 2014 (2014)
Road monitoring helps to control the regional traffic situation so as to adjust the traffic flow. Real-time panorama is conducive to timely treat traffic accidents and to greatly improve traffic capacity. This paper designs a 3D road scene monitoring
Externí odkaz:
https://doaj.org/article/81df6d2a33ef4d11a796df227703b26f
Publikováno v:
CMES-Computer Modeling in Engineering & Sciences; 2024, Vol. 138 Issue 1, p957-979, 23p