Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 206-212.doi: 10.11896/JsJkx.191100138
• Computer Graphics & Multimedia • Previous Articles Next Articles
YE Yang, ZHOU Qi-zheng, SHEN Ying and FAN Jing
CLC Number:
[1] LIU X X,HUANG J W,YAN H B.Automatic extraction method and application of single-wood canopy for high spatial resolution remote sensing.Journal of ZheJiang A and F University,2010,27(1):126-133. [2] 2POLLOCK R.The automatic recognition of individual trees in aerial images of forests based on a synthetic tree crown image model.University of British Columbia,1996. [3] LARSEN M,RUDEMO M.Optimizing templates for findingtrees in aerial photographs.Pattern Recognition Letters,1998,19(12):1153-1162. [4] WARNER T A,LEE J Y,MCGRAW J B.Delineation and identification of individual trees in the eastern deciduous forest.Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry,1998:10-12. [5] TARP-JOHANSEN M J.Automatic stem mapping in three dimensions by template matching from aerial photographs.Scandinavian Journal of Forest Research,2002,17(4):359-368. [6] WANG L,GONG P,BIGING G S.Individual tree-crown delineation and treetop detection in high-spatial-resolution aerial imagery.Photogrammetric Engineering & Remote Sensing,2004,70(3):351-357. [7] TOCHON G,FRET J B,VALERO S,et al.On the use of binary partition trees for the tree crown segmentation of tropical rainforest hyperspectral images.Remote Sensing of Environment,2015,159:318-331. [8] [8]SAMBUGARO M,COLPI C,MARZANO R,et al.Utilizzo del telerilevamento per l’analisidellabiodiversitàstrutturale:ilcaso studio dellaRiservaForestale di Clise (Asiago,VI)//Proceedings of the 17th ConferenzaNazionale ASITA.Riva del Garda,Italy,2013:5-7. [9] CULVENOR D S.TIDA:an algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery.Computers & Geosciences,2002,28(1):33-44. [10] ERIKSON M.Two preprocessing techniques based on grey level and geometric thickness to improve segmentation results.Pattern Recognition Letters,2006,27(3):160-166. [11] ZHEN Z,QUACKENBUSH L J,ZHANG L.Trends in automatic individual tree crown detection and delineation-evolution of lidardata.Remote Sensing,2016,8(4):333. [12] KASS M,WITKIN A,TERZOPOULOS D.Snakes:Active contour models.International Journal of Computer Vision,1988,1(4):321-331. [13] COHEN L D,COHEN I.A finite element method applied tonew active contour models and 3D reconstruction from cross sections//International Conference on Computer Vision.IEEE,1990:587-591. [14] JUMAAT A K,RAHMAN W E Z W A,IBRAHIM A,et al.Segmentation of masses from breast ultrasound images using parametric active contour algorithm.Procedia-Social and Behavioral Sciences,2010,8:640-647. [15] [15]KABOLIZADE M,EBADI H,AHMADI S.An improved snake model for automatic extraction of buildings from urban aerial images and LiDAR data.Computers Environment & Urban Systems,2010,34(5):435-441. |
[1] | CHEN Zhi-qiang, HAN Meng, LI Mu-hang, WU Hong-xin, ZHANG Xi-long. Survey of Concept Drift Handling Methods in Data Streams [J]. Computer Science, 2022, 49(9): 14-32. |
[2] | WANG Ming, WU Wen-fang, WANG Da-ling, FENG Shi, ZHANG Yi-fei. Generative Link Tree:A Counterfactual Explanation Generation Approach with High Data Fidelity [J]. Computer Science, 2022, 49(9): 33-40. |
[3] | ZHANG Jia, DONG Shou-bin. Cross-domain Recommendation Based on Review Aspect-level User Preference Transfer [J]. Computer Science, 2022, 49(9): 41-47. |
[4] | ZHOU Fang-quan, CHENG Wei-qing. Sequence Recommendation Based on Global Enhanced Graph Neural Network [J]. Computer Science, 2022, 49(9): 55-63. |
[5] | SONG Jie, LIANG Mei-yu, XUE Zhe, DU Jun-ping, KOU Fei-fei. Scientific Paper Heterogeneous Graph Node Representation Learning Method Based onUnsupervised Clustering Level [J]. Computer Science, 2022, 49(9): 64-69. |
[6] | CHAI Hui-min, ZHANG Yong, FANG Min. Aerial Target Grouping Method Based on Feature Similarity Clustering [J]. Computer Science, 2022, 49(9): 70-75. |
[7] | ZHENG Wen-ping, LIU Mei-lin, YANG Gui. Community Detection Algorithm Based on Node Stability and Neighbor Similarity [J]. Computer Science, 2022, 49(9): 83-91. |
[8] | LYU Xiao-feng, ZHAO Shu-liang, GAO Heng-da, WU Yong-liang, ZHANG Bao-qi. Short Texts Feautre Enrichment Method Based on Heterogeneous Information Network [J]. Computer Science, 2022, 49(9): 92-100. |
[9] | XU Tian-hui, GUO Qiang, ZHANG Cai-ming. Time Series Data Anomaly Detection Based on Total Variation Ratio Separation Distance [J]. Computer Science, 2022, 49(9): 101-110. |
[10] | NIE Xiu-shan, PAN Jia-nan, TAN Zhi-fang, LIU Xin-fang, GUO Jie, YIN Yi-long. Overview of Natural Language Video Localization [J]. Computer Science, 2022, 49(9): 111-122. |
[11] | CAO Xiao-wen, LIANG Mei-yu, LU Kang-kang. Fine-grained Semantic Reasoning Based Cross-media Dual-way Adversarial Hashing Learning Model [J]. Computer Science, 2022, 49(9): 123-131. |
[12] | ZHOU Xu, QIAN Sheng-sheng, LI Zhang-ming, FANG Quan, XU Chang-sheng. Dual Variational Multi-modal Attention Network for Incomplete Social Event Classification [J]. Computer Science, 2022, 49(9): 132-138. |
[13] | DAI Yu, XU Lin-feng. Cross-image Text Reading Method Based on Text Line Matching [J]. Computer Science, 2022, 49(9): 139-145. |
[14] | QU Qian-wen, CHE Xiao-ping, QU Chen-xin, LI Jin-ru. Study on Information Perception Based User Presence in Virtual Reality [J]. Computer Science, 2022, 49(9): 146-154. |
[15] | ZHOU Le-yuan, ZHANG Jian-hua, YUAN Tian-tian, CHEN Sheng-yong. Sequence-to-Sequence Chinese Continuous Sign Language Recognition and Translation with Multi- layer Attention Mechanism Fusion [J]. Computer Science, 2022, 49(9): 155-161. |
|