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.

Bibliografski detalji
Glavni autori: Dipro, Farhan Hasin, Simran, Sheikh Saif, Akhter, Mansura, Momo, Ramisa Fariha, Musharrat, Ramisa
Daljnji autori: Hossain, Muhammad Iqbal
Format: Disertacija
Jezik:English
Izdano: Brac University 2024
Teme:
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.
Online pristup:http://hdl.handle.net/10361/23617

Internet

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

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