|
国家林业和草原局/国家公园管理局. 2017年中国林业发展报告.[2019-05-05]. http://www.forestry.gov.cn/main/62/content-1086586.html.
|
|
National Forestry and Grassland Administration/National Park Administration. 2017 Forestry Development Report in China.[2019-05-05]. http://www.forestry.gov.cn/main/62/content-1086586.html. [in Chinese]
|
|
斯幸峰, 丁平. 欧美陆地鸟类监测的历史、现状与我国的对策. 生物多样性, 2013. 19 (3): 303- 310.
|
|
Si X F , Ding P . History, status of monitoring land birds in Europe and America and countermeasures of China. Biodiversity Science, 2013. 19 (3): 303- 310.
|
|
约翰·马敬能,卡伦·菲力普斯,何芬奇,等. 2000.中国鸟类野外手册:中文版.长沙:湖南教育出版社.
|
|
Mackinnon J, Phillipps K, He F Q, et al. 2000. A Field Guide to the Birds of China. Changsha: Hunan Education Publishing House.[in Chinese]
|
|
Branson S, Van Horn G, Belongie S, et al. 2014. Bird species categorization using pose normalized deep convolutional nets. arXiv preprint, arXiv: 1406.2952.
|
|
Canterbury G E , Martin T E , Petit D R , et al. Bird communities and habitat as ecological indicators of forest condition in regional monitoring. Conservation Biology, 2000. 14 (2): 544- 558.
doi: 10.1046/j.1523-1739.2000.98235.x
|
|
Cheng C , Fu Y W , Jiang Y G , et al. Dual skipping networks. Conference on Computer Vision and Pattern Recognition, IEEE, 2018. 4071- 4079.
|
|
Cohen J . A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 1960. 20 (1): 37- 46.
doi: 10.1177/001316446002000104
|
|
Dubey A , Gupta O , Guo P , et al. Pairwise confusion for fine-grained visual classification. European Conference on Computer Vision, Springer, 2018. 70- 86.
|
|
Farrell R , Oza O , Zhang N , et al. Birdlets:Subordinate categorization using volumetric primitives and pose-normalized appearance. International Conference on Computer Vision, IEEE, 2011. 161- 168.
|
|
Gao Y , Mosalam K M . Deep transfer learning for image-based structural damage recognition. Computer-Aided Civil and Infrastructure Engineering, 2018. 33 (9): 748- 768.
doi: 10.1111/mice.12363
|
|
Huang G , Liu Z , Van Der Maaten L , et al. Densely connected convolutional networks. Conference on Computer Vision and Pattern Recognition, IEEE, 2017. 4700- 4708.
|
|
Huang S , Xu Z , Tao D , et al. Part-stacked CNN for fine-grained visual categorization. Conference on Computer Vision and Pattern Recognition, IEEE, 2016. 1173- 1182.
|
|
Ioffe S , Szegedy C . Batch normalization:Accelerating deep network training by reducing internal covariate shift. International Conference on Machine Learning, MIT Press, 2015. 448- 456.
|
|
Keskar N S, Mudigere D, Nocedal J, et al. 2017. On large-batch training for deep learning: Generalization gap and sharp minima. International Conference on Learning Representations.arXiv preprint, arXiv: 1609.04836.
|
|
Koskimies P . Birds as a tool in environmental monitoring. Annales Zoologici Fennici, 1989. 26 (3): 153- 166.
|
|
Krause J , Sapp B , Howard A , et al. The unreasonable effectiveness of noisy data for fine-grained recognition. European Conference on Computer Vision, Springer, 2016. 301- 320.
|
|
Lin T Y , RoyChowdhury A , Maji S . Bilinear convolutional neural networks for fine-grained visual recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. 40 (6): 1309- 1322.
doi: 10.1109/TPAMI.2017.2723400
|
|
Long J , Shelhamer E , Darrell T . Fully convolutional networks for semantic segmentation. Conference on Computer Vision and Pattern Recognition, IEEE, 2015. 3431- 3440.
|
|
Loshchilov I, Hutter F. 2017. SGDR: Stochastic gradient descent with warm restarts. The Fifth International Conference on Learning Representations. OpenReview.net. https://openreview.net/forum?id=skq89scxx.
|
|
Lu Y , Yin J , Chen Z , et al. Revealing detail along the visual hierarchy:neural clustering preserves acuity from V1 to V4. Neuron, 2018. 98 (2): 417- 428.
doi: 10.1016/j.neuron.2018.03.009
|
|
Marini A , Turatti A J , Britto A S , et al. Visual and acoustic identification of bird species. International Conference on Acoustics, Speech and Signal Processing, IEEE, 2015. 2309- 2313.
|
|
Martinez-Munoz G , Larios N , Mortensen E , et al. Dictionary-free categorization of very similar objects via stacked evidence trees. Conference on Computer Vision and Pattern Recognition, IEEE, 2009. 549- 556.
|
|
Nadimpalli U D , Price R R , Hall S G , et al. A comparison of image processing techniques for bird recognition. Biotechnology Progress, 2006. 22 (1): 9- 13.
doi: 10.1021/bp0500922
|
|
Savard J P L , Clergeau P , Mennechez G . Biodiversity concepts and urban ecosystems. Landscape and Urban Planning, 2000. 48 (3/4): 131- 142.
|
|
Sharif Razavian A , Azizpour H , Sullivan J , et al. CNN features off-the-shelf:an astounding baseline for recognition. Conference on Computer Vision and Pattern Recognition Workshops, IEEE, 2014. 806- 813.
|
|
Szegedy C , Liu W , Jia Y , et al. Going deeper with convolutions. Conference on Computer Vision and Pattern Recognition, IEEE, 2015. 1- 9.
|
|
Szegedy C , Vanhoucke V , Ioffe S , et al. Rethinking the inception architecture for computer vision. Conference on Computer Vision and Pattern Recognition, IEEE, 2016. 2818- 2826.
|
|
Tan C , Sun F , Kong T , et al. A survey on deep transfer learning. International Conference on Artificial Neural Networks, Springer, 2018. 270- 279.
|
|
Van Horn G , Branson S , Farrell R , et al. Building a bird recognition app and large scale dataset with citizen scientists:The fine print in fine-grained dataset collection. Conference on Computer Vision and Pattern Recognition, IEEE, 2015. 595- 604.
|
|
Wei X S , Xie C W , Wu J , et al. Mask-CNN:Localizing parts and selecting descriptors for fine-grained bird species categorization. Pattern Recognition, 2018. 76, 704- 714.
doi: 10.1016/j.patcog.2017.10.002
|
|
Welinder P, Branson S, Wah C, et al. 2010. The Caltech-UCSD Birds-200 dataset. California Institute of Technology. Technical Report CNS-TR2010-001-2010.
|
|
Xie L , Tian Q , Zhang B . Feature normalization for part-based image classification. International Conference on Image Processing, IEEE, 2013. 2607- 2611.
|
|
Yin C , Zhang L , Liu J . Pixel saliency based encoding for fine-grained image classification. Chinese Conference on Pattern Recognition and Computer Vision, Springer, 2018. 274- 285.
|
|
Yosinski J , Clune J , Bengio Y , et al. How transferable are features in deep neural networks?. Advances in Neural Information Processing Systems, 2014. 3320- 3328.
|
|
Zhang N , Donahue J , Girshick R , et al. Part-based R-CNNs for fine-grained category detection. European Conference on Computer Vision, Springer, 2014. 834- 849.
|
|
Zhang N , Farrell R , Darrell T . Pose pooling kernels for sub-category recognition. Conference on Computer Vision and Pattern Recognition, IEEE, 2012. 3665- 3672.
|