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.

Xehetasun bibliografikoak
Egile Nagusiak: Dipro, Farhan Hasin, Simran, Sheikh Saif, Akhter, Mansura, Momo, Ramisa Fariha, Musharrat, Ramisa
Beste egile batzuk: Hossain, Muhammad Iqbal
Formatua: Thesis
Hizkuntza:English
Argitaratua: Brac University 2024
Gaiak:
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.
Sarrera elektronikoa:http://hdl.handle.net/10361/23617

Internet

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

Antzeko izenburuak