object-detection-classification

版本 1.0.1 (29.2 MB) 作者: Muhammad Rashid

Object Detection and Classifications paper codes

http://thecomputervision.com/publications.php

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更新时间 2022/7/6

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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.

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创建方式 R2018a

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AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Classification >

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codes

无法下载基于 GitHub 默认分支的版本

版本	已发布	发行说明
1.0.1	2022/7/6	Updated Codes
1.0.0	2019/3/21		下载

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。

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.
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
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} }

object-detection-classification