Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Liye Mei"'
Autor:
Mengping Long, Yueyun Weng, Liye Mei, Dingchao Yang, Shubin Wei, Guanxiong Meng, Wanyue Zhao, Sheng Liu, Du Wang, Yiqiang Liu, Hui Shen, Jianxuan Hou, Yu Xu, Liang Tao, Fuling Zhou, Hongwei Chen, Taobo Hu, Cheng Lei
Publikováno v:
Advanced Sensor Research, Vol 3, Iss 8, Pp n/a-n/a (2024)
Abstract A serous effusion is a buildup of extra fluid in the serous cavities including pleural, peritoneal, and pericardial cavities. It is important to distinguish benign reactive effusions from effusions caused by malignant proliferation in cytopa
Externí odkaz:
https://doaj.org/article/776d8573e0174a9e9b91103955b93379
Autor:
Chuan Xu, Haonan Yu, Liye Mei, Ying Wang, Jian Huang, Wenying Du, Shuangtong Jin, Xinliu Li, Minglin Yu, Wei Yang, Xinghua Li
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 6174-6188 (2024)
Remote sensing (RS) image change detection (CD) methods based on deep learning, such as convolutional neural networks (CNNs) and transformers, are still spatial domain-based image processing methods by nature, and their detection accuracy is strongly
Externí odkaz:
https://doaj.org/article/21af7a11a4a949b78486f889019125cd
Autor:
Shiwei Chen, Liye Mei
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
Introduction: Optical and SAR image matching is one of the fields within multi-sensor imaging and fusion. It is crucial for various applications such as disaster response, environmental monitoring, and urban planning, as it enables comprehensive and
Externí odkaz:
https://doaj.org/article/8f84e72e962b48338d9ff77f791ce96d
Publikováno v:
Entropy, Vol 26, Iss 6, p 445 (2024)
Salient object detection (SOD) aims to accurately identify significant geographical objects in remote sensing images (RSI), providing reliable support and guidance for extensive geographical information analyses and decisions. However, SOD in RSI fac
Externí odkaz:
https://doaj.org/article/871db23f8a2245238ad04b989f772f4b
Autor:
Jingwen Zhang, Jingwen Deng, Jin Huang, Liye Mei, Ni Liao, Feng Yao, Cheng Lei, Shengrong Sun, Yimin Zhang
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
PurposeThe aim of this study was to investigate the value of a deep learning model (DLM) based on breast tumor ultrasound image segmentation in predicting pathological response to neoadjuvant chemotherapy (NAC) in breast cancer.MethodsThe dataset con
Externí odkaz:
https://doaj.org/article/2dfc5a9300494dab9bf7eadb49b66331
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 12, Iss 9, p 382 (2023)
Road crack detection is one of the important issues in the field of traffic safety and urban planning. Currently, road damage varies in type and scale, and often has different sizes and depths, making the detection task more challenging. To address t
Externí odkaz:
https://doaj.org/article/1fcffb9615bc42a2ac1b368863373fbd
Publikováno v:
Drones, Vol 7, Iss 8, p 517 (2023)
Fusing infrared and visible images taken by an unmanned aerial vehicle (UAV) is a challenging task, since infrared images distinguish the target from the background by the difference in infrared radiation, while the low resolution also produces a les
Externí odkaz:
https://doaj.org/article/853e84ce106442af81cd15fce731a4d8
Publikováno v:
IEEE Photonics Journal, Vol 14, Iss 1, Pp 1-9 (2022)
To solve the matching problems caused by the large intensity difference between the multi-source images and the nonlinear radiation distortion, we present a multi-source image matching approach that considers the orientation of the phase sharpness. F
Externí odkaz:
https://doaj.org/article/a034d1184aff49b8ac86982e72678358
Publikováno v:
Geo-spatial Information Science, Vol 0, Iss 0, Pp 1-14 (2021)
Level set method has been extensively used for image segmentation, which is a key technology of water extraction. However, one of the problems of the level-set method is how to find the appropriate initial surface parameters, which will affect the ac
Externí odkaz:
https://doaj.org/article/b2c4960577cc484eafe1a8cbfae7d3e5
Publikováno v:
Remote Sensing, Vol 15, Iss 8, p 1958 (2023)
Building change detection (BCD) using high-resolution remote sensing images aims to identify change areas during different time periods, which is a significant research focus in urbanization. Deep learning methods are capable of yielding impressive B
Externí odkaz:
https://doaj.org/article/27f091f86e78449f8db95bdc9a1ae51b