[1] 牛善栋,方斌.中国耕地保护制度70年:历史嬗变、现实探源及路径优化[J].中国土地科学, 2019, 33(10): 1-12. [2] 卢绍婷,周俊晖.农村乱占耕地建房整治方法研究与系统实现[J].国土资源信息化, 2021(2): 48-53. [3] LI M,STEIN A,KMD B.A bayesian characterization of urban land use configurations from VHR remote sensing images[J]. International journal of applied earth observation and geoinformation, 2020, 10:102175. [4] 陈琳,刘清华.城镇和农村住宅用地使用现状及整治建议——以湖北省钟祥市为例[J]. 中国土地, 2020(5): 52-53. [5] 吴家杰,黄霞,刘锟铭.农村乱占耕地建房疑似违法图斑自动提取研究[J].江西测绘, 2020(4):37-38, 41. [6] 夏晓鸿,潘俊国,董海潮,等.全省农村土地综合监管机制创新调研报告[J].浙江国土资源, 2018(11): 35-37. [7] 周建国. 农村耕地非法转为宅基地的问题与对策[J].贵州农业科学, 2010, 38(2): 183-188. [8] 王丹,张璐,柴燕妮.基于深度学习的乱占耕地建房疑似图斑自动提取方法研究[J].测绘与空间地理信息,2022,45(6): 51-53,57. [9] YU H, YANG Z, TAN L, et al.Methods and datasets on semantic segmentation: A review[J]. Neurocomputing, 2018, 304, 82-103. [10] CROMMELINCK S,KOEVA M,YANG M Y,et al.Application of deep learning for delineation of visible cadastral boundaries from remote sensing imagery[J]. Remote sensing, 2019,11(21): 2505. [11] LECUN Y, BENGIO Y, HINTON G.Deep learning[J]. Nature, 2015, 521:436-444. [12] LONG J,SHELHAMER E,DARRELL T.Fully convolutional networks for semantic segmentation[J]. IEEE transactions on pattern analysis and machine intelligence, 2015,39(4): 640-651. [13] PERSELLO C, STEIN A.Deep fully convolutional networks for the detection of informal settlements in VHR images[J]. IEEE geoscience and remote sensing letters, 2017,14(12): 2325-2329. [14] 范荣双,陈洋,徐启恒,等.基于深度学习的高分辨率遥感影像建筑物提取方法[J].测绘学报, 2019, 48(1):34-41. [15] 季顺平,田思琦,张驰.利用全空洞卷积神经元网络进行城市土地覆盖分类与变化检测[J].武汉大学学报(信息科学版), 2020, 45(2):233-241. [16] 王舒洋,慕晓冬,杨东方,等.融合高阶信息的遥感影像建筑物自动提取[J].光学精密工程, 2019, 27(11):2474-2483. [17] LIU R, KUFFER M, PERSELLO C.The temporal dynamics of slums employing a CNN-based change detection approach[J]. Remote sensing, 2019, 11(23):2844. [18] XIA X, PERSELLO C, KOEVA M.Deep fully convolutional networks for cadastral boundary detection from UAV images[J]. Remote sensing, 2019, 11(14):1725. |