State-of-the-Art Object Recognition Techniques: A Comparative Study-Reference-Cited by-同舟云学术

State-of-the-Art Object Recognition Techniques: A Comparative Study

Published:2020 Issue: Volume: Page:925-932
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Goel Rohini,Sharma Avinash,Kapoor Rajiv

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-0751-9_85

Reference34 articles.

1. Shokoufandeh, A., Keselman, Y., Demirci, M.F., Macrini, D., Dickinson, S.J.: Many to many feature matching in object recognition: a review of three approaches. IET Comput. Vis. (2012)

2. Lillywhite, K, Archibald, J.: A feature construction method for general object recognition. Pattern Recognit. (2013)

3. Martin, L., Tuysuzojlu, A., Karl, W.C., Ishwa, P.: Learning based object identification and segmentation using dual energy CT images for security. IEEE Trans. Image Process. (2015)

4. Ehrenmann, M., Ambela, D., Steinhaus, P., Dillmann, R.: A comparison of four fast vision based object recognition methods for programming by demonstration Applications. In: CIEEE International Conference on Robotics and Automations (2000)

5. Khurana, K., Awasthi, R.: Techniques of object recognition in images and multi-object detection. Int. J. Adv. Res. Comput. Eng. Technol. (2013)

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparative Analysis of Deep Learning Approaches for Detecting Copy-Move Forgery;2024 International Conference on Computational Intelligence and Computing Applications (ICCICA);2024-05-23

2. An Efficient Object and Railway Track Recognition in Thermal Images Using Deep Learning;Lecture Notes in Electrical Engineering;2022

3. A robust approach for object recognition in real time thermal images using deep learning;AIP Conference Proceedings;2022

4. Broad-UNet: Multi-scale feature learning for nowcasting tasks;Neural Networks;2021-12

5. Motion Model and Filtering Techniques for Scaled Vehicle Localization with Fiducial Marker Detection;Advances in Intelligent Systems and Computing;2021-07-31