object-detection-classification

Versión 1.0.1 (29,2 MB) por Muhammad Rashid

Object Detection and Classifications paper codes

http://thecomputervision.com/publications.php

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Actualizado 6 jul 2022

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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

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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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Se creó con R2018a

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Versión	Publicado	Notas de la versión
1.0.1	6 jul 2022	Updated Codes
1.0.0	21 mar 2019		Descargar

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.

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

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