ARCHIVES

1. S. Zhang, C.Wang, S.C.Chan, X.Wei and C H. Ho. A New object detection tracking and recognition approaches for video surveillance
over camera network, IEEE Sensors Journal, vol. 15, no. 5, pp. 2679-2691, 2015.
2. M. Kowalski, M. Kastek, H. Polakowski, N. Palka, M. Piszczek, and M. Szustakowski. Multispectral concealed weapon detection i n
visible, Journal of infrared and terahertz, pp. 91020T-91020T-7.
3. M. C. Kemp. Millimetre wave and terahertz technology for the detection of concealed threats a review, Journal of image process, pp
64020D-64020D-19.
4. R. C. Luo, C.-C. Yih, and K. L. Su, “Multisensor fusion and integration: approaches, applications, and future research directions,” IEEE
Sensors Journal, vol. 2, no. 2, pp. 107-119, 2002.
5. H. Zhou, W. Wang, C. Chen, and Y. Zheng, “A low-noise, large-dynamic-range-enhanced amplifier based on JFET buffering input and
JFET bootstrap structure,” IEEE Sensors Journal, vol. 15, no. 4, pp. 2101-2105, 2015.
6. M. Kowalski, M. Kastek, M. Piszczek, M. Życzkowski, and M. Szustakowski, “Harmless screening of humans for the detection of
concealed objects,” Safety and Security Engineering VI, vol. 151, pp. 215, 2015.
7. D. Woo, I. Nam, and H. Lee, “Smart reset control for wide-dynamic-range LWIR FPAs,” IEEE Sensors Journal, vol. 11, no. 1, pp. 131-
136, 2011.
8. M. Mahesh, “Airport full-body scanners,” Journal of the American College of Radiology, vol. 7, no. 5, pp. 379-381, 2010.
9. M. Kastek, T. Piątkowski, R. Dulski, M. Chamberland, P. Lagueux, and V. Farley, "Multispectral and hyperspectral measurements of
soldier's camouflage equipment." pp. 83820K-83820K-14.
10. M. Kowalski, M. Kastek, N. Palka, H. Polakowski, M. Szustakowski, and M. Piszczek, “Investigation of concealed objects detect ion in
visible, infrared and terahertz ranges of radiation,” Photonics Letters of Poland, vol. 5, no. 4, pp. pp. 167-169, 2013.
11. G. Verma and S. Prakash, "A Study Towards Current Trends Issues and Challenges in Internet of Things (IoT) based System for Intelligent
Energy Management", 2019 4th International Conference on Information Systems and Computer Networks (ISCON), pp. 358-365, 2019.
12. P. Dollár, R. Appel, S. Belongie and P. Perona, Fast feature pyramids for object detection Transactions on Pattern Analysis and Machine
Intelligence, vol. 36, no. 8, pp. 1532-1545, 2014.
13. J. Yang and G. Yang, "Modified Convolutional Neural Network Based on Dropout and the Stochastic Gradient Descent Optimizer Key
Laboratory of Advanced Manufacturing Technology of Ministry of Education", Guizhou University, 2018.
14. X. Rong, C. Yi and Y. Tian, "Recognizing text-based traffic guide panels with cascaded localization network", European Conference on
Computer Vision, pp. 109-121, 2016, October.
15. Deven Pawar, Mihir Raul, Pranav Raut and Sharmila Gaikwad, "Recognize Objects for Visually Impaired using Computer
Vision", International Journal of Recent Technology and Engineering (IJRTE), vol. 8, no. 6, March 2020, ISSN 2277-3878.
16. Yuming He et al., "Research on Text Detection and Recognition based on OCR Recognition Technology", IEEE 3rd International
Conference on Information Systems and Computer Aided Education (ICISCAE 2020).
17. M. Liao, B. Shi and X. Bai, "Textboxes++: A single-shot oriented scene text detector", IEEE Transactions on Image Processing, vol. 27,
no. 8, pp. 3676-3690, 2018.
18. Wei, H.; Laszewski, M.; Kehtarnavaz, "N. Deep Learning-Based Person Detection and Classification for Far Field Video
Surveillance", In Proceedings of the 2018 IEEE 13th Dallas Circuits and Systems Conference, Dallas, TX, USA, 12 November 2018.
19. U. Qidwai, and C.-H. Chen, Digital image processing: an algorithmic approach with MATLAB: CRC press, 2009.
20. G. Piella, “A general framework for multiresolution image fusion: from pixels to regions,” Information Fusion, vol. 4, no. 4, pp. 259-280,
2003.
21. V. Naidu, and J. Raol, “Pixel-level image fusion using wavelets and principal component analysis,” Defence Science Journal, vol. 58, no.
3, pp. 338, 2008.