D-ARTNET22 V1: a neural network framework against stolen digital artworks getting Non-Fungible Token (NFT) labels

D-ARTNET22 V1: a neural network framework against stolen digital artworks getting Non-Fungible Token (NFT) labels

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Bibliografiska uppgifter
Huvudupphovsmän: Dipro, Farhan Hasin, Simran, Sheikh Saif, Akhter, Mansura, Momo, Ramisa Fariha, Musharrat, Ramisa
Övriga upphovsmän: Hossain, Muhammad Iqbal
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2024
Ämnen:
Non-Fungible Tokens (NFT)
Digital art
Convolutional Neural Net- works (CNN)
You Only Look Once (YOLO)
Adobe Photoshop CC
Image forgery
Image classification
Object detection
Neural networks (Computer science)
Image processing > Digital techniques.
Länkar:http://hdl.handle.net/10361/23617

Internet

http://hdl.handle.net/10361/23617

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