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Shin, D., Lee, J., Lee, J. and Yoo, H.-J. (2017) 14.2 DNPU: An 8.1TOPS/W Reconfigurable CNN-RNN Processor for General-Purpose Deep Neural Networks. IEEE International Solid-State Circuits Conference, San Francisco, 5-9 February 2017.
https://doi.org/10.1109/ISSCC.2017.7870350

has been cited by the following article:

• TITLE: A Survey on Matching of Shoeprint with Reference Footwear in Forensic Study

  AUTHORS: Md. Al Mamun, Morium Akter, Mohammad Shorif Uddin

  KEYWORDS: Forensic Study, Footwear, Shoeprint, Feature Extraction, Segmentation

  JOURNAL NAME: Journal of Computer and Communications, Vol.7 No.9, September 4, 2019

  ABSTRACT: Footwear impression marks on the outside surface of shoes are distinctive patterns and an important forensic clue often found at offense scenes. However, in many cases, the footwear mark is treated with improper evidence due to difficulties in visibility and understanding. This paper presents a thorough review of matching algorithms along with enhancement techniques of shoeprint in the forensic study. Finally, it shows some research directions.