Open Access
| Issue |
E3S Web Conf.
Volume 426, 2023
The 5th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2023)
|
|
|---|---|---|
| Article Number | 01014 | |
| Number of page(s) | 6 | |
| Section | Integrated Sustainable Science and Technology Innovation | |
| DOI | https://doi.org/10.1051/e3sconf/202342601014 | |
| Published online | 15 September 2023 | |
- M. Salonen, K. Vapalahti, K. Tiira, A. Mäki-Tanila, and H. Lohi, Breed differences of heritable behaviour traits in cats, Nature (2019) [Google Scholar]
- L. Plitman, P. Cerná, M.J. Farnworth, R.M.A. Packer, and D.A. Gunn-Moore, Motivation of Owners to Purchase Pedigree Cats, with Specific Focus on the Acquisition of Brachycephalic Cats, MDPI (2019) [Google Scholar]
- Y. Zhang, J. Gao, H. Zhou, Breeds Classification with Deep Convolutional Neural Networks, 12th International Conference on Machine Learning and Computing (2020) [Google Scholar]
- T. Karlita, R. Asmara, N.A. Choirunisa, and F. Setyorini, Cat Breeds Classification Using Compound Model Scaling Convolutional Neural Networks, in International Conference on Applied Science and Technology on Social Science, iCAST (2021) [Google Scholar]
- M. Tan, and Q.V. Le, EfficientNetV2: Smaller Models and Faster Training, (Arxiv, 2021) [Google Scholar]
- Wang, I. Hung, Mahardi, K.C. Lee, S.L. Chang, Predicting the Breed of Dogs and Cats with Fine-Tuned Keras Applications, Intelligent Automation & Soft Computing (2021) [Google Scholar]
- S.C. Huang, A. Pareek, S. Seyyedi, I. Banerjee, and M.P. Lungren, Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guideline, (npj Digital Medicine, 2020) [Google Scholar]
- M.A.A. Fawwaz, K.N. Ramadhani, and F. Sthevanie, Klasifikasi Ras pada Kucing menggunakan Algoritma Convolutional Neural Network (CNN), in e-Proceeding of Engineering, 8 (2021) [Google Scholar]
- O. Gano, Gano Cat Breed Image Collection (Kaggle, 2022) [Google Scholar]
- Mahardi, I.H. Wang, K.C. Lee, and S.L, Chang, Images Classification of Dogs and Cats using Fine- Tuned VGG Models, in 2nd IEEE Eurasia Conference on IOT, Communication and Engineering (2020) [Google Scholar]
- A. Imanuel, and D.H. Setiabudi, Penerapan Convolutional Neural Network dengan Pre-Trained Model Xception untuk Meningkatkan Akurasi dalam Mengidentifikasi Jenis Ras Kucing, 10 (INFRA, 2022) [Google Scholar]
- L.O.A.S. Sagala, Klasifikasi Cats and Dogs dengan metode CNN dalam Fungsi Aktivasi relu, sigmoid, softmax, softplus, softsign, dan selu, (2022) [Google Scholar]
- K. Ali, Z.A. Shaikh, A.A. Khan, and A.A. Laghari, Multiclass skin cancer classification using EfficientNets – a first step towards preventing skin cancer, (Elsevier, 2022) [Google Scholar]
- D. Kitaguchi, N. Takeshita, H. Matsuzaki, T. Oda, M. Watanabe, K. Mori, E. Kobayashi, and M. Ito, automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: Experimental research, (Elsevier, 2020) [Google Scholar]
- L. Wang, K. He, X. Feng, and X. Ma, Multilayer feature fusion with parallel convolutional block for fine-grained image classification, (IEEE, 2019) [Google Scholar]
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