Modified ResNet50 model and semantic segmentation based image co-saliency detection
*Anuj MangalCorresponding authoranuj.mangal@gla.ac.inDepartment of Computer Engineering & ApplicationsGLA UniversityMathura, Uttar Pradesh, IndiaView full profile → , Hitendra Garghitendra.garg@gla.ac.inDepartment of Computer Engineering & ApplicationsGLA UniversityMathura, Uttar Pradesh, IndiaView full profile → , Charul Bhatnagarcharul@gla.ac.inDepartment of Computer Engineering & ApplicationsGLA UniversityMathura, Uttar Pradesh, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Published Online:
- 11 Nov 2023
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1331
- Pages:
- 1035–1042
Abstract
Keywords
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References
[1] Zhang, K., Dong, M., Liu, B., Yuan, X. T., & Liu, Q., DeepACG: Co-Saliency Detection via Semantic-aware Contrast Gromov-Wasserstein Distance. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 13703-13712 (2021).
[2] Sharma, P., Sharma, M. S. P., & Tomar, R. S. : A new approach for image segmentation using improved k-means and ROI saliency map.Journal of Information and Optimization Sciences, 38(6), 927-935 (2017).
[3] Qian, X., Zeng, Y., Wang, W., & Zhang, Q., Co-saliency Detection Guided by Group Weakly Supervised Learning. IEEE Transactions on Multimedia (2022).
[4] Tsai, C. C., Hsu, K. J., Lin, Y. Y., Qian, X., & Chuang, Y. Y., Deep co-saliency detection via stacked autoencoder-enabled fusion and self-trained cnns. IEEE Transactions on Multimedia, 22(4), 1016-1031 (2019).
[5] Gao, G., Zhao, W., Liu, Q., & Wang, Y., Co-saliency detection with co-attention fully convolutional network. IEEE Transactions on Circuits and Systems for Video Technology, 31(3), 877-889 (2020).
[6] Qin, X., Zhang, Z., Huang, C., Gao, C., Dehghan, M., & Jagersand, M., Basnet: Boundary-aware salient object detection. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 7479-7489 (2019).
[7] Ye, L., Liu, Z., Li, J., Zhao, W. L., & Shen, L., Co-saliency detection via co-salient object discovery and recovery. IEEE Signal Processing Letters, 22(11), 2073-2077 (2015).
[8] Fu, H., Cao, X., & Tu, Z., Cluster-based co-saliency detection. IEEE Transactions on Image Processing, 22(10), 3766-3778 (2013).
[9] Wei, L., Zhao, S., Bourahla, O. E. F., Li, X., & Wu, F., Group-wise deep co-saliency detection (2017). arXiv preprint arXiv:1707.07381.
[10] Qian, X., Zeng, Y., Wang, W., & Zhang, Q., Co-saliency Detection Guided by Group Weakly Supervised Learning. IEEE Transactions on Multimedia (2022).
[11] Zhang, D., Han, J., Han, J., & Shao, L., Cosaliency detection based on intrasaliency prior transfer and deep intersaliency mining. IEEE transactions on neural networks and learning systems, 27(6), 1163-1176 (2015).
[12] Wei, L., Zhao, S., Bourahla, O. E. F., Li, X., & Wu, F., Group-wise deep co-saliency detection (2017). arXiv preprint arXiv:1707.07381.
[13] Zhang, Z., Jin, W., Xu, J., & Cheng, M. M., Gradient-induced co-saliency detection. In European Conference on Computer Vision, pp. 455-472. Springer, Cham (2020, August).
[14] Zhang, K., Li, T., Shen, S., Liu, B., Chen, J., & Liu, Q., Adaptive graph convolutional network with attention graph clustering for co-saliency detection. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 9050-9059 (2020).
[15] Simonyan, K., & Zisserman, A., Very deep convolutional networks for large-scale image recognition (2014). arXiv preprint arXiv:1409.1556.
[16] Li, T., Zhang, K., Shen, S., Liu, B., Liu, Q., & Li, Z., Image co-saliency detection and instance co-segmentation using attention graph clustering based graph convolutional network. IEEE Transactions on Multimedia (2021).
[17] Sahoo, D. K., Das, A., Mohanty, M. N., & Mishra, S., Brain tumor detection using in painting and deep ensemble model. Journal of Information and Optimization Sciences, 43(8), 1925-1933 (2022).




