ARCHIVES

[1]. Adadi, A., &Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access, 6,52138–52160.
https://doi.org/10.1109/AC CESS.2018.2870052.
[2]. Ahani, A., Nilashi, M., Ibrahim, O., Sanzogni, L., &Weaven, S. (2019). Market segmentation and travel choice prediction in Spa hotels through
TripAdvisor’s online reviews. International Journal of Hospitality Management, 80,
5277. https://doi.org/10.1016/j.ijhm.2019.01.003 .
[3] Amorós, L., Hafiz, S. M., Lee, K., &Tol, M. C. (2020). Gimme that model!: A trusted ML model trading protocol. arXiv:2003.00610 [cs].
http://arxiv.org/abs/2003.00610 4. Assaf, R., & Schumann, A. (2019).
[4]. Explainable deep neural networks for multivariate time series predictions. Proceedings of the 28th International Joint Conference on Artificial
Intelligence, 6488–6490. https://doi.org/10.24963/ijcai.2019/932 .
[5]. Bastan, M., Ramisa, A., &Tek, M. (2020). Cross-modal fashion product search with transformer-based Embeddings. CVPR Workshop - 3rd workshop
on Computer Vision for Fashion, Art and Design, Seattle: Washington.
[6]. Brynjolfsson, E., & McAfee, A. (2017).The business of artificial intelligence. Harvard Business Review, 1–20.
[7]. Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Rahmati, A., Xiao, C., Prakash, A., Kohno, T., & Song, D. (2018). Robust physical- world attacks on
deep learning visual classification. IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018,1625– 1634.
https://doi.org/10.1109/CVPR .2018.00175 .
[8]. Halidu, M. K., Bagheri-Zadeh, P., Sheikh-Akbari, A., &Behringer, R. (2019, June).Pca in the context of face recognition with the image enlargement
techniques.In 2019 8th Mediterranean Conference on Embedded Computing (MECO) (pp. 1–5).
[9]. Wijaya, I. G. P. S., Husodo, A. Y.,&Arimbawa, I. W. A. (2016, October).Real time face recognition using DCT coefficients based face descriptor. In
2016 International Conference on Informatics and Computing (ICIC) (pp. 142–147).
[10]. Jiang, C., Wang, M., Tang, X., & Mao, R.(2019, November). Face recognition method based on sparse representation and featurefusion. In 2019
Chinese Automation Congress (CAC) (pp.396–400).
[11]. Xiao, J., &Weiwei, G. (2019, October).Face recognition algorithm based on Prewitt and convolutional neural network. In 2019 3rdInternational
Conference on Electronic Information Technology and Computer Engineering (EITCE) (pp.2007–2009).
[12]. Kerımbekov, Y., & Bılge, H. Ş. (2017,May). Face recognition via Lorentzian metric. In 2017 25th Signal Processing and Communications Applications Conference (SIU) (pp. 1–4).
[13]. Chang, L., Yang, J., Li, S., Xu, H., Liu,K., & Huang, C. (2018, November). Face recognition based on stacked convolutionalautoencoder and sparse
representation. In 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) (pp. 1–4).
[14]. Nandhini, R., Duraimurugan, N.,&Chokkalingam, S. P. (2019). Face recognition based attendance system. International Journal ofEngineering and Advanced Technology (IJEAT), 8(3S). 15. Khan, M., Chakraborty, S., Astya, R.,&Khepra, S. (2019, October). Face Detection and Recognition Using OpenCV. In 2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (pp. 116–119).
[15]. Khan, M., Chakraborty, S., Astya, R., &Khepra, S. (2019, October). Face Detection and Recognition Using OpenCV. In 2019International Conference on Computing,Communication, and Intelligent Systems (ICCCIS) (pp. 116–119).