Paper
29 April 2022 Recognizing birds by image recognition
Bochen Pan, Yujin Wang, Ruming Zhong
Author Affiliations +
Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 122470V (2022) https://doi.org/10.1117/12.2637648
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China
Abstract
In this work, three algorithms (HOG with SVM, VGG, ResNet) are chosen to perform better image recognition on different categories of birds. HOG with SVM performs worse than ResNetwith SVM because HOG is better at recognizing objects than identifying categories of objects. Hyper-parameters in HOG and SVM will affect the accuracy. (Bochen). To improve the accuracy of the image recognition, the VGG algorithm is adopted with different hyper-parameters. Yujin Wang employs “Deep residual learning for image recognition” from He K, Zhang X, Ren S, et al to show his understanding of the ResNet algorithm. He will test different hyperparameters in ResNet and show readers how they will affect the results.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bochen Pan, Yujin Wang, and Ruming Zhong "Recognizing birds by image recognition", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 122470V (29 April 2022); https://doi.org/10.1117/12.2637648
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KEYWORDS
Data modeling

Detection and tracking algorithms

Binary data

Image processing

Computer programming

Data processing

Image classification

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