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- W4385202233 abstract "Remote Sensing imagery security plays an important role in different fields like navy, coastal areas, marine. Among all these, vessel detection and tracking in these fields is sensitive. Thus, privacy preservation and identification of vessel data using remote sensing is important. But locating it manually can be difficult, with the advent of cryptographic hash function, deep learning technology and image processing. The existing technique for the proposed system is YOLOv2, but the limitation is that the model struggles when there are groups of small objects and lack of privacy preservation. There are better detecting and tracking techniques such as YOLOv3, U-Net, and privacy preservation using secure hashing algorithm (SHA)-256 which is most widely used and best hashing algorithm. The proposed system can be used to monitor vessel traffic in a designated area, such as a port or harbour, and can also be used to detect vessels in real time for security and safety purposes." @default.
- W4385202233 created "2023-07-25" @default.
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- W4385202233 date "2023-01-01" @default.
- W4385202233 modified "2023-09-26" @default.
- W4385202233 title "Privacy Preservation of Maritime Vessel Data Using SHA-256" @default.
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- W4385202233 doi "https://doi.org/10.1007/978-981-99-3878-0_15" @default.
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