1 |
郭香凤, 向进乐, 李秀珍, 等. 贮藏温度对西兰花净菜品质的影响[J]. 农业机械学报, 2008, 39(2): 201-204.
|
2 |
夏永泉, 李耀斌, 曾莎. 基于HSI颜色空间的植物叶片病斑提取方法[J]. 江苏农业科学, 2015(08): 420-422.
|
3 |
高理文, 林小桦. 基于L*a*b*彩色空间和局域动态阈值的药用植物叶片图像分割[J]. 计算机应用与软件, 2014, (1): 232-235.
|
|
Gao L, Lin X. Segmentation of images of medicinal plant leaves based on L*a*b* colour space and local dynamic threshold[J]. Computer Applications and Software, 2014, (1): 232-235.
|
4 |
董晓辉. 基于多彩色空间的麦田监控图像分割技术研究[D]. 开封: 河南大学, 2015.
|
|
Dong X. Wheat mornitoring image segmatation technology using variety of color spaces[D]. Kaifeng: Henan Agricultural University, 2015.
|
5 |
魏丽冉, 岳峻, 李振波, 等. 基于核函数支持向量机的植物叶部病害多分类检测方法[J]. 农业机械学报, 2017, (S0): 166-171.
|
|
Wei L, Yue J, Li Z, et al. Multi-classification detection method of plant leaf disease based on kernel function SVM[J]. Transactions of the CSAM, 2017, (S0): 166-171.
|
6 |
周俊, 刘丽川, 杨继平. 基于K-均值聚类与小波分析的声发射信号去噪[J]. 石油化工高等学校学报, 2013, 26(3): 69-73.
|
|
Zhou J, Liu L, Yang J. Acoustic emission signal denoising based on K-means clustering and wavelet analysis[J]. Journal of Petrochemical Universities, 2013, 26(3): 69-73.
|
7 |
李先锋, 朱伟兴, 纪滨, 等. 基于图像处理和蚁群优化的形状特征选择与杂草识别[J]. 农业工程学报, 2010, 26(10): 178-182.
|
|
Li X, Zhu W, Ji B, et al. Shape feature selection and weed recognition based on image processing and ant colony optimization[J]. Transactions of the CSAE, 2010, 26(10): 178-182.
|
8 |
袁定帅, 陈洁, 赖晓芳, 等. 不同贮藏条件对西兰花感官品质及抗氧化物质的影响[J]. 食品科技, 2017, (4): 40-45.
|
|
Yuan D, Chen J, Lai X, et al. Effects of diifferent storage conditions on sensory quality and antioxidants of broccoli[J]. Food Science and Techonology, 2017, (4): 40-45.
|
9 |
Lee S H, Chan C S, Wilkin P, et al. Deep-plant: Plant identification with convolutional neural networks[C]// IEEE International Conference on Image Processing (ICIP), 2015: 452-456.
|
10 |
Dyrmann M, Karstoft H, Midtiby H S. Plant species classification using deep convolutional neural network[J]. Biosystems Engineering, 2016, 151: 72-80.
|
11 |
Too E C, Li Y, Njuki S, et al. A comparative study of fine-tuning deep learning models for plant disease identification[J]. Computers and Electronics in Agriculture, 2018, 161: 272-279.
|
12 |
Fuentes A, Yoon S, Kim S C, et al. A robust deep-learning-based detector for real-time tomato plant diseases and pests recognition[J]. Sensors, 2017, 17: 2022-2042.
|
13 |
李淼, 王敬贤, 李华龙, 等. 基于 CNN 和迁移学习的农作物病害识别方法研究[J]. 智慧农业, 2019, 1(3): 46-55.
|
|
Li M, Wang J, Li H, et al. Method for identifying crop disease based on CNN and transfer learning[J]. Smart Agriculture, 2019, 1(3): 46-55.
|
14 |
陈桂芬, 赵姗, 曹丽英, 等. 基于迁移学习与卷积神经网络的玉米植株病害识别[J]. 智慧农业, 2019, 1(2): 34-44.
|
|
Chen G, Zhao S, Cao L, et al. Corn plant disease recognition based on migration learning and convolutional neural network[J]. Smart Agriculture, 2019, 1(2): 34-44.
|
15 |
Fu Z, Robles-Kelly A. A quadratic programming approach to image labelling[J]. IET Computer Vision, 2009, 2(4): 193-207.
|
16 |
刘万军, 梁雪剑, 曲海成. 不同池化模型的卷积神经网络学习性能研究[J]. 中国图象图形学报, 2016, 21(9): 1178-1190.
|
|
Liu W, Liang X, Qu H. Learning performance of convolutional neural networks with different pooling models[J]. Journal of Image and Graphics, 2016, 21(9): 1178-1190.
|
17 |
李林, 顾进锋, 宋安捷, 等. 基于GPU的生态环境遥感评价模型并行化研究[J]. 农业机械学报, 2017(5): 140-146.
|
|
Li L, Gu J, Song A, et al. Parallelization on model of ecological environment remote sensing evaluation based GPU[J]. Transactions of the CSAM, 2017(5): 140-146.
|
18 |
He K, Zhang X, Ren S, et al. Identity mappings in deep residual networks[J]. Computer Science, 2016: 630-645.
|
19 |
Wang Y, Yang A, Chen X, et al. A deep learning approach for blind drift calibration of sensor networks[J]. IEEE Sensors Journal, 2017, 17(13): 4158-4171.
|
20 |
Gong L, Jiang S, Yang Z, et al. Automated pulmonary nodule detection in CT images using 3D deep squeeze-and-excitation networks[J]. International Journal of Computer Assisted Radiology and Surgery, 2019, 14(11): 1969-1979.
|
21 |
Zhou X, Jin K, Shang Y, et al. Visually interpretable representation learning for depression recognition from facial images[J]. IEEE Transactions on Affective Computing, 2018, DOI: 10.1109/TAFFC.2018.2828819.
doi: 10.1109/TAFFC.2018.2828819
|
22 |
Wurfl T, Hoffmann M, Christlein V, et al. Deep learning computed tomography: Learning projection-domain weights from image Domain in limited angle problems[J]. IEEE Transactions on Medical Imaging, 2018, 37(6): 1454-1463.
|
23 |
Fan Y C, Chen Y C, Chou S Y. Vivid-DIBR based 2D-3D image conversion system for 3D display[J]. Journal of Display Technology, 2017, 10(10): 887-898.
|
24 |
Philipp P, Felix V. Optimal approximation of piecewise smooth functions using deep ReLU neural networks[J]. Neural Networks, 2018, 108: 296-330.
|
25 |
Cai H, Yang Z, Cao X, et al. A new iterative triclass thresholding technique in image segmentation[J]. IEEE Transactions on Image Processing, 2014, 23(3): 1038-1046.
|
26 |
Hao G, Xu W. Image segmentation using Quantum-behaved partical swarm optimization algorithm[J]. Computer Engineering and Applications, 2007, 43(33): 831-835.
|
27 |
李长缨, 简元才, 杜广岑, 等. 青花菜耐贮性鉴定方法和标准[J]. 华北农学报, 1999, 14(4):134-136.
|
|
Li C, Jian Y, Du G, et al. Appraising method and standard for storage durability in broccoli[J]. Acta Agriculturae Boreali-Sinica, 1999, 14(4): 134-136.
|
28 |
侯格贤, 吴成柯. 图像分割质量评价方法研究[J]. 中国图象图形学报, 2000, 5A(1): 39-43.
|
|
Hou G, Wu C. Researches on evaluation methods for images segmentation[J]. Journal of Image and Graphics, 2000, 5A(1): 39-43.
|