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

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