机构

• 自动化研究所 [4]
• 地理科学与资源研究所 [2]
• 长春光学精密机械与物... [2]
• 南海海洋研究所 [1]
• 计算技术研究所 [1]
• 深海科学与工程研究所 [1]
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采集方式

• OAI收割 [12]

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• 期刊论文 [10]
• 会议论文 [2]

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• 2025 [2]
• 2024 [1]
• 2022 [2]
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• 2015 [1]
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• Engineerin... [1]
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筛选

浏览/检索结果: 共12条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择发表日期升序发表日期降序题名升序题名降序提交时间升序提交时间降序作者升序作者降序 TopoRF-Net: Topology-Aware Road Segmentation in Multi-Resolution Remote Sensing via Multi-Receptive Field Adaptation 期刊论文  OAI收割 SENSORS, 2025, 卷号: 25, 期号: 24, 页码: 7428 作者:  Fu, Junjie;  Wang, Chenliang;  Lv, Hongchen;  Lu, Hao;  Shi, Wenjiao   |  收藏  |  浏览/下载：5/0  |  提交时间：2026/01/21 remote sensing imagery  semantic segmentation  road extraction  multi-receptive field  structural connectivity  topology-aware loss   Identifying localized heat zones in urban heat islands from a hill and saddle perspective 期刊论文  OAI收割 SUSTAINABLE CITIES AND SOCIETY, 2025, 卷号: 118, 页码: 13 作者:  Yu, Wenbo;  Yang, Jun;  Ren, Jiayi;  Zhang, Zhenchao;  Sun, Dongqi   |  收藏  |  浏览/下载：63/0  |  提交时间：2025/03/03 Urban heat island  Watershed algorithm  Structural segmentation  Driving mechanism  Jinan city   Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery 期刊论文  OAI收割 BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 卷号: 87, 页码: 10 作者:  Wu, Zhiying;  Lau, Chun Yin;  Zhou, Qianang;  Wu, Jinlin;  Wang, Yuxi   |  收藏  |  浏览/下载：65/0  |  提交时间：2023/12/21 Transformer  Semi-supervised segmentation  Structural similarity  Surgical instrument segmentation   Wheat-Net: An Automatic Dense Wheat Spike Segmentation Method Based on an Optimized Hybrid Task Cascade Model 期刊论文  OAI收割 FRONTIERS IN PLANT SCIENCE, 2022, 卷号: 13, 页码: 13 作者:  Zhang, Jiajing;  Min, An;  Steffenson, Brian J.;  Su, Wen-Hao;  Hirsch, Cory D.   |  收藏  |  浏览/下载：43/0  |  提交时间：2022/06/06 wheat spike  instance segmentation  Hybrid Task Cascade model  challenging dataset  non-structural field   Structure attention co-training neural network for neovascularization segmentation in intravascular optical coherence tomography 期刊论文  OAI收割 MEDICAL PHYSICS, 2022, 页码: 16 作者:  Wu, Xiangjun   |  收藏  |  浏览/下载：53/0  |  提交时间：2022/03/17 co-training  IVOCT  neovascularization segmentation  structural attention mechanism   Along-strike segmentation of the South China Sea margin imposed by inherited pre-rift basement structures 期刊论文  OAI收割 EARTH AND PLANETARY SCIENCE LETTERS, 2020, 卷号: 530, 期号: 1, 页码: 14 作者:  Zhao, Fang;  Alves, Tiago M.;  Xia, Shaohong;  Li, Wei;  Wang, Lei   |  收藏  |  浏览/下载：72/0  |  提交时间：2020/03/16 South China Sea  structural inheritance  faults  magmatism  continental rifting  margin segmentation   Along-strike segmentation of the South China Sea margin imposed by inherited pre-rift basement structures 期刊论文  OAI收割 EARTH AND PLANETARY SCIENCE LETTERS, 2020, 卷号: 530, 页码: 115862 作者:  Zhao, Fang;  Alves, Tiago M.;  Xia, Shaohong;  Li, Wei;  Wang, Lei   |  收藏  |  浏览/下载：75/0  |  提交时间：2020/09/22 South China Sea  structural inheritance  faults  magmatism  continental rifting  margin segmentation   Separating the Structural Components of Maize for Field Phenotyping Using Terrestrial LiDAR Data and Deep Convolutional Neural Networks 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 卷号: 58, 期号: 4, 页码: 2644-2658 作者:  Jin, Shichao;  Su, Yanjun;  Gao, Shang;  Wu, Fangfang;  Ma, Qin   |  收藏  |  浏览/下载：68/0  |  提交时间：2022/03/01 Classification  deep learning  LiDAR  phenotype  segmentation  structural components   Automatic segmentation of the lateral geniculate nucleus: Application to control and glaucoma patients 期刊论文  OAI收割 JOURNAL OF NEUROSCIENCE METHODS, 2015, 卷号: 255, 页码: 104-114 作者:  Wang, Jieqiong;  Miao, Wen;  Li, Jing 收藏  |  浏览/下载：66/0  |  提交时间：2016/01/18 Automatic segmentation  LGN  Structural MRI  Vision   TextureGrow: Object recognition and segmentation with limit prior knowledge (EI CONFERENCE) 会议论文  OAI收割 2011 International Conference on Network Computing and Information Security, NCIS 2011, May 14, 2011 - May 15, 2011, Guilin, Guangxi, China Yao Z.; Han Q. 收藏  |  浏览/下载：57/0  |  提交时间：2013/03/25 In this paper we present a new method for automatically visual recognition and semantic segmentation of photographs. Our automatically and rapidly approach based on Cellular Automation. Most of the analysis and description of recognition and segmentation are based on statistical or structural properties of this attribute  most of them need plenty of samples and prior Knowledge. In this paper  within a few evident samples (not too many)  we can first get the texture feature of each component and the structures  then select the approximately location randomly of the objects or patches of them  then we use the Cellular Automata algorithm to "grow" based on texture of different objects. The grow progress will stop When texture grow to the boundary. By this steps a new method is found which allow us use very few samples and low lever experience and get a rapidly and accuracy way to recognize and segment objects. We found that this new propose gives competitive results with limited experience and samples. 2011 IEEE.