The code contains descriptive matlab functions
1-Deepnet algo contains the code for features extraction using neural networks and then feature selection adn then feature vector finalization
2- classifier training
3- Labels prediction
4- classifying video frames into classes from Caltech-101 dataset
引用格式
Rashid, Muhammad, et al. “Object Detection and Classification: a Joint Selection and Fusion Strategy of Deep Convolutional Neural Network and SIFT Point Features.” Multimedia Tools and Applications, Springer Nature, Dec. 2018, doi:10.1007/s11042-018-7031-0.
查看更多格式
| MLA |
Rashid, Muhammad, et al. “Object Detection and Classification: a Joint Selection and Fusion Strategy of Deep Convolutional Neural Network and SIFT Point Features.” Multimedia Tools and Applications, Springer Nature, Dec. 2018, doi:10.1007/s11042-018-7031-0.
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| APA |
Rashid, M., Khan, M. A., Sharif, M., Raza, M., Sarfraz, M. M., & Afza, F. (2018). Object detection and classification: a joint selection and fusion strategy of deep convolutional neural network and SIFT point features. Multimedia Tools and Applications. Springer Nature. Retrieved from https://doi.org/10.1007%2Fs11042-018-7031-0
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| BibTeX |
@article{Rashid_2018,
doi = {10.1007/s11042-018-7031-0},
url = {https://doi.org/10.1007%2Fs11042-018-7031-0},
year = 2018,
month = {dec},
publisher = {Springer Nature},
author = {Muhammad Rashid and Muhammad Attique Khan and Muhammad Sharif and Mudassar Raza and Muhammad Masood Sarfraz and Farhat Afza},
title = {Object detection and classification: a joint selection and fusion strategy of deep convolutional neural network and {SIFT} point features},
journal = {Multimedia Tools and Applications}
}
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