1 |
H. Xiao, K. Rasul, and R. Vollgraf, "Fashion-mnist: A novel image dataset for benchmarking machine learning algorithms," arXiv preprint arXiv:1708.07747, 2017.
|
2 |
A. Krizhevsky and G. Hinton, "Learning multiple layers of features from tiny images," p.7, 2009.
|
3 |
Y. Xu and R. Goodacre, "On splitting training and validation set: A comparative study of cross-validation, bootstrap and systematic sampling for estimating the generalization performance of supervised learning," Journal of Analysis and Testing, Vol.2, No.3, pp.249-262, 2018.
DOI
|
4 |
M. Ozuysal, M. Calonder, V. Lepetit, and P. Fua, "Fast keypoint recognition using random ferns," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.32, No.3, pp.448-461, 2009.
DOI
|
5 |
A. Angelova, A. Krizhevsky, V. Vanhoucke, A. Ogale, and D. Ferguson, "Real-time pedestrian detection with deep network cascades," 2015.
|
6 |
R. Kohavi, "A study of cross-validation and bootstrap for accuracy estimation and model selection," Ijcai, Vol.14. No.2, pp.1137-1145, 1995.
|
7 |
A. K. Jain and A. Vailaya, "Image retrieval using color and shape," Pattern Recognition, Vol.29, No.8, pp.1233-1244, 1996.
DOI
|
8 |
G. Pass, and R. Zabih, "Histogram refinement for content-based image retrieval," Proceedings Third IEEE Workshop on Applications of Computer Vision, WACV'96. IEEE, 1996.
|
9 |
L. Rokach and O. Maimon, "Clustering methods," Data Mining and Knowledge Discovery Handbook. Springer, Boston, MA, pp.321-352, 2005.
|
10 |
R. Xu and D. Wunsch, "Survey of clustering algorithms," IEEE Transactions on Neural Networks, Vol.16, No.3, pp.645-678, 2005.
DOI
|
11 |
R. Bro and A. K. Smilde, "Principal component analysis," Analytical Methods, Vol.6, No.9, pp.2812-2831, 2014.
DOI
|
12 |
B. Froba and A. Ernst, "Face detection with the modified census transform," Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings, IEEE, 2004.
|
13 |
S. Mani, A. Sankaran, S. Tamilselvam, and A. Sethi, "Coverage testing of deep learning models using dataset characterization," arXiv preprint arXiv:1911.07309, 2019.
|
14 |
A. Sharif Razavian, H. Azizpour, J. Sullivan, and S. Carlsson, "CNN features off-the-shelf: An astounding baseline for recognition," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2014.
|
15 |
N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). Vol.1. IEEE, 2005.
|
16 |
R. Lienhart and J. Maydt, "An extended set of haar-like features for rapid object detection," Proceedings. International Conference on Image Processing, Vol.1. IEEE, 2002.
|
17 |
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun, "Overfeat: Integrated recognition, localization and detection using convolutional networks," arXiv preprint arXiv:1312.6229, 2013.
|
18 |
M. Flickner, et al, "Query by image and video content: The QBIC system," Computer, Vol.28, No.9, pp.23-32, 1995.
DOI
|
19 |
F. Milletari, N. Navab, and S. A. Ahmadi, "V-net: Fully convolutional neural networks for volumetric medical image segmentation," 2016 Fourth International Conference on 3D Vision (3DV). IEEE, 2016.
|
20 |
A. Ferdowsi and W. Saad, "Deep learning for signal authentication and security in massive internet-of-things systems," IEEE Transactions on Communications, Vol.67, No.2, pp.1371-1387, 2018.
DOI
|
21 |
L. Liu, C. Shen, and A. Van Den Hengel, "The treasure beneath convolutional layers: Cross-convolutional-layer pooling for image classification," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015.
|
22 |
T. Lindeberg, "Scale invariant feature transform," pp.10491, 2012.
|
23 |
S. Yadav and S. Shukla, "Analysis of k-fold cross-validation over hold-out validation on colossal datasets for quality classification," 2016 IEEE 6th International Conference on Advanced Computing (IACC), IEEE, 2016.
|
24 |
D. ping Tian, "A review on image feature extraction and representation techniques," International Journal of Multimedia and Ubiquitous Engineering, Vol.8, No.4, pp.385-396, 2013.
|
25 |
J. Huang, S.R. Kumar, M. Mitra, W. Zhu, and R. Zabih, "Image indexing using color correlograms," Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 1997.
|
26 |
G. Chandrashekar and F. Sahin, "A survey on feature selection methods," Computers & Electrical Engineering, Vol.40, No.1, pp.16-28, 2014.
DOI
|
27 |
M. Bojarski, et al., "End to end learning for self-driving cars," arXiv preprint arXiv:1604.07316, 2016.
|
28 |
T. Ojala, M. Pietikainen, and D. Harwood, "A comparative study of texture measures with classification based on featured distributions," Pattern Recognition, Vol.29, No.1, pp.51-59, 1996.
DOI
|
29 |
A. Esteva, et al, "Dermatologist-level classification of skin cancer with deep neural networks," Nature, Vol.542, No.7639, pp.115-118, 2017.
DOI
|
30 |
S. Na, L. Xumin, and G. Yong, "Research on k-means clustering algorithm: An improved k-means clustering algorithm," 2010 Third International Symposium on intelligent Information Technology and Security Informatics, IEEE, 2010.
|
31 |
T. M. Kodinariya and P. R. Makwana, "Review on determining number of Cluster in K-Means Clustering," International Journal, Vol.1, No.6, pp.90-95, 2013.
|
32 |
J. Xue, C. Lee, S. G.Wakeham, and R. A. Armstronga, "Using principal components analysis (PCA) with cluster analysis to study the organic geochemistry of sinking particles in the ocean," Organic Geochemistry, Vol.42, No.4, pp.356-367, 2011.
DOI
|