MobileNets: Efficient Convolutional Neural Network for Identification of Protected Birds
How to cite (IJASEIT) :
K. Lawson and A. Vines, Global Impacts of the Illegal Wildlife Trade, no. February. 2014.
A. Haryanta, D. N. Adhiasto, and N. Hardianto, Pendataan & Pengenalan Jenis Satwa Liar di Pasar Burung Yang Sering diperdagangkan. 2013.
P. P. Gavali, M. Prachi, A. Mhetre, M. Neha, and C. Patil, “Bird Species Identification using Deep Learning,” Int. J. Eng. Res. Technol., vol. 8, no. 04, pp. 68-72, 2019.
E. R. Bush, S. E. Baker, and D. W. Macdonald, “Global trade in exotic pets 2006-2012,” Conserv. Biol., vol. 28, no. 3, pp. 663-676, 2014.
P. Jepson and R. J. Ladle, “Bird-keeping in Indonesia: Conservation impacts and the potential for substitution-based conservation responses,” Oryx, vol. 39, no. 4, pp. 442-448, 2005.
J. Eaton et al., “Trade-driven extinctions and near-extinctions of avian taxa in Sundaic Indonesia,” Forktail, vol. 31, no. January 2015, pp. 0-12, 2016.
S. D. Das and A. Kumar, “Bird Species Classification using Transfer Learning with Multistage Training,” pp. 1-9, 2018.
L. Wilson-Wilde, “Wildlife crime: A global problem,” Forensic Sci. Med. Pathol., vol. 6, no. 3, pp. 221-222, 2010.
V. Nijman, “An overview of international wildlife trade from Southeast Asia,” Biodivers. Conserv., vol. 19, no. 4, pp. 1101-1114, 2010.
R. Dirzo, H. Young, M. Galetti, G. Ceballos, J. Nick, and B. Collen, “Defaunation in the antropocene_dirzo2014.pdf,” Science (80-. )., vol. 345, no. 6195, p. 401, 2014.
I. A. Ciampitti and J. Albers, “Agricultural Mobile Apps: A review and update of ID apps,” 2015.
O. Russakovsky et al., “ImageNet Large Scale Visual Recognition Challenge,” Int. J. Comput. Vis., vol. 115, no. 3, pp. 211-252, 2015.
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman, “The pascal visual object classes (VOC) challenge,” Int. J. Comput. Vis., vol. 88, no. 2, pp. 303-338, 2010.
T. Y. Lin et al., “Microsoft COCO: Common objects in context,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 8693 LNCS, no. PART V, pp. 740-755, 2014.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,” Adv. neural Inf. Process. Syst., pp. 1097-1105, 2012.
Y. Lecun, L. Bottou, Y. Bengio, and P. Ha, “GradientBased Learning Applied to DocumentRecognition,” in Proceedings of the IEEE, 1998, no. November, pp. 1-46.
S. G. Lee, Y. Sung, Y. G. Kim, and E. Y. Cha, “Variations of AlexNet and GoogLeNet to improve Korean character recognition performance,” J. Inf. Process. Syst., vol. 14, no. 1, pp. 205-217, 2018.
B. P. Tóth and B. Czeba, “Convolutional neural networks for large-scale bird song classification in noisy environment,” CEUR Workshop Proc., vol. 1609, pp. 560-568, 2016.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting,” J. Mach. Learn. Res., vol. 15, pp. 1929-1958, 2014.
A. Jain and B. K. Sharma, “Analysis of Activation Functions for Convolutional Neural Network based MNIST Handwritten Character Recognition,” Int. J. Adv. Stud. Sci. Res., vol. 3, no. 9, pp. 68-74, 2018.
W. S. Eka Putra, A. Y. Wijaya, and R. Soelaiman, “Klasifikasi Citra Menggunakan Convolutional Neural Network (CNN) pada Caltech 101,” J. Tek. ITS, vol. 5, no. 1, pp. A65-A69, 2016.
A. Santoso and G. Ariyanto, “Implementasi Deep Learning Berbasis Keras Untuk Pengenalan Wajah,” Emit. J. Tek. Elektro, vol. 18, no. 01, pp. 15-21, 2018.
K. Simonyan and A. Zisserman, “Very Deep Convolutional Networks for Large-Scale Image Recognition,” 2014, pp. 1-14.
C. K. Dewa, A. L. Fadhilah, and A. Afiahayati, “Convolutional Neural Networks for Handwritten Javanese Character Recognition,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 12, no. 1, p. 83, 2018
A. G. Howard et al., “MobileNet s: Efficient Convolutional Neural Networks for Mobile Vision Applications,” 2017.
B. Zhao, X. Wu, J. Feng, Q. Peng, and S. Yan, “Diversified Visual Attention Networks for Fine-Grained Object Classification,” IEEE Trans. Multimed., vol. 19, no. 6, pp. 1245-1256, 2017.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).