Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang et al., 3D ShapeNets: A Deep Representation for Volumetric Shapes, Proceedings of CVPR, 2015.

A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang et al., ShapeNet: An Information-Rich 3D Model Repository, Proceedings of CVPR, 2015.

N. Kumar, P. N. Belhumeur, A. Biswas, D. W. Jacobs, W. J. Kress et al., Leafsnap: A computer vision system for automatic plant species identification, Proceedings of ECCV, 2012.

A. Dai, A. X. Chang, M. Savva, M. Halber, and T. A. Funkhouser, ScanNet: Richly Annotated 3D Reconstructions of Indoor Scenes. CVPR, pp.5828-5839, 2017.

P. Dewan, Words versus Pictures: Leveraging the Research on Visual Communication Partnership: the Canadian Journal of Library and Information Practice and Research, vol.10, pp.1-10, 2015.

K. Ricanek and T. Tesafaye, MORPH: A Longitudinal Image Database of Normal Adult Age-Progression, Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition, pp.341-345, 2006.

P. Sharma and R. Reilly, A Color Face Image database for Benchmarking of Automatic Face Detection Algorithms, Proceedings of 4 th EURASIP Conference on Video/Image Processing and Multimedia Communications, 2003.

J. Dieng, W. Dong, R. Socher, L. Li, K. Li et al., ImageNet: A Large-Scale Hierarchical Image Database, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2009.

B. Russell and A. Torralba, Building a database of 3D scenes from user annotations, Proceedings of CVPR, 2009.

L. Lenc and P. Král, Unconstrained Facial Images: Database for Face Recognition under Real-World Conditions, Advances in Artificial Intelligence and Its Applications. MICAI 2015. Lecture Notes in Computer Science, 9414, 2015.

B. Zhou, A. Khosla, A. Lapedriza, A. Torralba, and A. Oliva, Places: An Image Database for Deep Scene Understanding, Proceedings of CoRR, 2016.

P. Shilane, P. Min, M. Kazhdan, and T. Funkhouser, The Princeton shape benchmark, Shape Modeling Applications. IEEE, 2004.

D. Rifai, A. Maeder, and L. Liyanage, A Content-Based-Image-Retrieval Approach for Medical Image Repositories, Proceedings of the 8th Australasian Workshop on Health Informatics and Knowledge Management (HIKM)

A. Sydney, , 2015.

M. Macko, E. Miko?ajewska, Z. Szczepa?sk, B. Augusty?ska, and D. Miko?ajewski, Repository of Images for Reverse Engineering and Medical Simulation Purposes, Medical and Biological Sciences, vol.30, issue.3, pp.23-29, 2016.

S. Nakamura, M. Sawada, Y. Aoki, P. Hartono, and S. Hashimoto, Flower Image Database Construction and Its Retrieval, Proceedings of the 7th Korea-Japan joint Workshop on Computer Vision, 2001.

T. Okamura, M. Toguro, M. Iwasaki, P. Hartono, and S. Hashimoto, Construction of a Flower Image Database with Feature and Index-based Searching Mechanism, 5th International Workshop on Image Analysis for Multimedia Interactive Services, 2004.

A. C. Martin and W. J. Harvey, The Global Pollen Project: A New Tool for Pollen Identification and the Dissemination of Physical Reference Collections, Methods in Ecology and Evolution, vol.8, pp.892-897, 2017.

Z. Lian, A. Godil, B. Bustos, M. Daoudi, J. Hermans et al., SHREC '11 track: Shape retrieval on non-rigid 3D watertight meshes, Proceedings of the ACM workshop on 3D object retrieval, 2011.

B. Li, A. Godil, M. Aono, X. Bai, T. Furuya et al., SHREC'12 Track: Generic 3D Shape Retrieval, Proceedings of Eurographics Workshop on 3D Object Retrieval, pp.119-126, 2012.

B. Li, Y. Lu, C. Li, A. Godil, T. Schreck et al., SHREC'14 Track: Large Scale Comprehensive 3D Shape Retrieval, proceedings of 7 th Eurographics Workshop on 3D Object Retrieval. France. 131-140. 6 th April, 2014.

J. Krause, M. Stark, J. Deng, and L. Fei-fei, 3D Object Representations for Fine-Grained Categorization, Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCVW), 2013.

A. Janoch, S. Karayev, Y. Jia, J. T. Barron, M. Fritz et al., A category-level 3D object dataset: Putting the Kinect to work, Consumer Depth Cameras for Computer Vision, pp.141-165, 2013.

D. Chudasama, T. Patel, and S. Joshi, Image Segmentation using Morphological Operations International Journal of Computer Applications, vol.117, issue.8, pp.16-19, 2015.

S. Kaur and I. Singh, Comparison between Edge Detection Techniques, International Journal of Computer Applications, vol.145, issue.15, pp.15-18, 2016.

A. Kabade and V. G. Sangam, Canny edge detection algorithm, International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE), vol.5, issue.5, 1292.

S. Vijayarani and M. Vinupriya, Performance Analysis of Canny and Sobel Edge Detection Algorithms in Image Mining, International Journal of Innovative Research in Computer and Communication Engineering. l, issue.8, pp.1760-1767, 2013.

M. H. Shokhan, An Efficient Approach For Improving Canny Edge Detection Algorithm, International Journal of Advances in Engineering & Technology, vol.7, issue.1, pp.59-65, 2014.

A. Eshaghzadeh, Canny edge detection algorithm application for analysis of the potential field map, 2016.

G. Papandreou, L. C. Chen, and K. Murphy, Weakly-and semi-supervised learning of a DCNN for semantic image segmentation, 2015.

L. C. Chen, G. Papandreou, I. Kokkinos, and . Deeplab, Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs, 2016.

M. P. Dhore, V. M. Thakare, and K. V. Kale, Morphological Segmentation in Document Image Analysis for Text Document, Images International Journal of Computational Intelligence Techniques, vol.2, issue.2, pp.35-43, 2011.

A. P. Vartak and V. Mankar, Morphological Image Segmentation Analysis, International Journal of Computer Science and Applications, vol.6, issue.2, pp.161-165, 2013.

R. Sharma and R. Sharma, Image Segmentation using Morphological Operations for Automatic Region Growing, International Journal of Computer Science and Information Technologies, vol.4, issue.6, pp.844-847, 2013.

M. H. Siddiqi, I. Ahmad, and S. Sulaiman, Weed Recognition Based on Erosion and Dilation Segmentation Algorithm, Proceedings of International Conference on Education Technology and Computer, pp.224-228, 2009.

T. Liu, R. Liu, P. , and S. Pan, Improved Canny Algorithm for Edge Detection of Core Image. The Open Automation and Control Systems Journal, vol.6, pp.426-432, 2014.

Y. Yeh, L. Yang, M. Watson, N. Goodman, and P. Hanrahan, Synthesizing Open Worlds with Constraints Using Locally Annealed Reversible Jump MCMC, ACM Transactions on Graphics, 2012.

S. Ravi and A. Khan, Morphological Operations for Image Processing: Understanding and its Applications, Proceedings of 2 nd National Conference on VLSI, Signal processing & Communications NCVSComs, 2013.

Y. Duan, J. S. Edwards, and Y. K. Dwivedi, Artificial intelligence for decision making in the era of Big Dataevolution, challenges and research agenda, International Journal of Information Management, vol.48, pp.63-71, 2019.