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.

Detalles Bibliográficos
Autores principales: Dipro, Farhan Hasin, Simran, Sheikh Saif, Akhter, Mansura, Momo, Ramisa Fariha, Musharrat, Ramisa
Otros Autores: Hossain, Muhammad Iqbal
Formato: Tesis
Lenguaje:English
Publicado: Brac University 2024
Materias:
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.
Acceso en línea:http://hdl.handle.net/10361/23617

Internet

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

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