1 |
张创创, 袁帅坤, 霍克坤. 影响番茄生产效益的因素[J]. 湖北农机化, 2020(12): 33-34.
|
|
ZHANG C, YUAN S, HUO K. Factors affecting tomato production efficiency[J]. Hubei Agricultural Mechanization, 2020(12): 33-34.
|
2 |
王建玺, 宁菲菲, 鲁书喜. 基于支持向量机的苹果叶部病害识别方法研究[J]. 山东农业科学, 2015, 47(7): 122-125, 141.
|
|
WANG J, NING F, LU S. Study on apple leaf disease identification method based on support vector machine[J]. Shandong Agricultural Science, 2015, 47(7): 122-125, 141.
|
3 |
秦丰, 刘东霞, 孙炳达, 等. 基于图像处理技术的四种苜蓿叶部病害的识别[J]. 中国农业大学学报, 2016, 21(10): 65-75.
|
|
QIN F, LIU D, SUN B, et al. Recognition of four different alfalfa leaf diseases based on image processing technology[J]. Journal of China Agricultural University, 2016, 21 (10): 65-75.
|
4 |
夏永泉, 李耀斌, 李晨. 基于图像处理技术的小麦叶部病害识别研究[J]. 科技通报, 2016, 32(4): 92-95.
|
|
XIA Y, LI Y, LI C. Recognition of wheat leaf disease based on image processing technology[J]. Science and Technology Bulletin, 2016, 32(4): 92-95.
|
5 |
刘婷婷, 王婷, 胡林. 基于卷积神经网络的水稻纹枯病图像识别[J]. 中国水稻科学, 2019, 33(1): 90-94.
|
|
LIU T, WANG T, HU L. Rhizocotonia Solani recognition algorithm based on convolution neural network[J]. China Journal of Rice Science, 2019, 33(1): 90-94.
|
6 |
WU Y. Identification of maize leaf diseases based on convolutional neural network[J]. Journal of Physics: Conference Series, 2021, 1748(3): ID 032004.
|
7 |
丁瑞, 周平. 基于卷积神经网络的典型农作物叶病害识别算法[J]. 包装学报, 2018, 10(6): 74-80.
|
|
DING R, ZHOU P. Identification of typical crop leaf diseases based on convolutional neural network[J]. Packaging Journal, 2018, 10(6): 74-80.
|
8 |
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.
|
9 |
WAHEED A, MUSKAN G, GUPTA D, et al. An optimized dense convolutional neural network model for disease recognition and classification in corn leaf[J]. Computers and Electronics in Agriculture, 2020, 175: ID 105456.
|
10 |
常江, 管声启, 师红宇, 等. 基于改进生成对抗网络和MobileNetV3的带钢缺陷分类[J]. 激光与光电子学进展, 2021, 58(4): 221-226.
|
|
CHANG J, GUAN S, SHI H, et al. Strip defect classification based on improved generative adversarial networks and MobileNetV3[J]. Laser & Optoelectronics Progress, 2021, 58(4): 221-226.
|
11 |
FAYE M, CHEN B, KANE A S. Plant disease detection with deep learning and feature extraction using plant village[J]. Journal of Computer and Communications, 2020, 8(6):10-22.
|
12 |
WANG X, ZHANG C, ZHANG S. Multiscale convolutional neural networks with attention for plant species recognition[J]. Computational Intelligence and Neuroscience, 2021, 2021: ID 5529905.
|
13 |
ZOHAIB M, SHUN F, QUOC V. Spectral images based environmental sound classification using CNN with meaningful data augmentation[J]. Applied Acoustics, 2021, 172 :ID 107581.
|
14 |
陆健强, 林佳翰, 黄仲强, 等. 基于Mixup算法和卷积神经网络的柑橘黄龙病果实识别研究[J]. 华南农业大学学报, 2021, 42(3): 94-101.
|
|
LU J, LIN J, HUANG Z, et al. Identification of citrus fruit infected with Huanglongbing based on Mixup algorithm and convolutional neural network[J]. Journal of South China Agricultural University, 2021, 42(3): 94-101.
|
15 |
葛丽君. 混合beta分布的建模方法研究[J]. 南国博览, 2019(4): 166.
|
16 |
易强, 李成娟, 李宝清, 等. 基于改进MobileNetV1网络的野外车辆识别[J]. 工业控制计算机, 2020, 33(7): 104-107.
|
|
YI Q, LI C, LI B, et al. Field vehicle recognition based on improved MobileNetV1 network[J]. Industrial Control Computer, 2020, 33(7): 104-107.
|
17 |
陈智超, 焦海宁, 杨杰, 等. 基于改进MobileNetV2的垃圾图像分类算法[J]. 浙江大学学报(工学版), 2021, 55(8): 1490-1499.
|
|
CHEN Z, JIAO H, YANG J, et al. Garbage image classification algorithm based on improved MobileNetV2[J]. Journal of Zhejiang University (Engineering Edition), 2021, 55(8): 1490-1499.
|
18 |
LI X, SHEN X, ZHOU Y, et al. Classification of breast cancer histopathological images using interleaved DenseNet with SENet (IDSNet)[J]. PLoS One, 2020, 15(5): ID e0232127
|
19 |
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 crop disease identification based on CNN and transfer learning[J]. Smart Agriculture, 2019, 1(3): 46-55.
|
20 |
MOON J, HOSSAIN M B, CHON K H. AR and ARMA model order selection for time-series modeling with ImageNet classification[J]. Signal Processing, 2021, 183(10): ID 108026.
|
21 |
姚燕, 胡立坤, 郭军. 基于深度迁移网络MobileNetV3的地形识别[J]. 广西大学学报(自然科学版), 2021, 46(4): 996-1007.
|
|
YAO Y, HU L, GUO J. Terrain recognition based on deep migration network MobileNetV3[J]. Journal of Guangxi University (Natural Science Edition), 2021, 46 (4): 996-1007.
|
22 |
AMAHAN P A, VILLARICA M V, VINLUAN A A. Technical analysis of Twitter data in preparation of prediction using multilayer perceptron algorithm[C]// Proceedings of 2021 4th International Conference on Data Science and Information Technology (DSIT 2021). New York, USA: Association for Computing Machinery, 2021: 120-124.
|
23 |
KUMAR V, SINGH R, DUA Y. Morphologically dilated convolutional neural network for hyperspectral image classification[J]. Signal Processing: Image Communication, 2022, 101: ID 116549.
|
24 |
耿海波. 基于U-Net模型的单声道唱声分离研究[D]. 乌鲁木齐: 新疆大学, 2020.
|
|
GENG H. Research on mono singing sound separation based on U-Net model[D]. Urumqi: Xinjiang University, 2020.
|
25 |
MABUNI D, BABU S A. High accurate and a variant of k-fold cross validation technique for predicting the decision tree classifier accuracy[J]. International Journal of Innovative Technology and Exploring Engineering, 2021, 10(2): 105-110.
|