Defense against adversarial attack in image recognition
Deep neural networks were found to be extremely useful and perform exceedingly well in machine learning tasks such as computer vision, speech recognition, natural language processing and in various domains such as healthcare system and autonomous car system. The high accuracy exhibited by the deep l...
Saved in:
Main Author: | Ng, Shi Qi |
---|---|
Format: | Final Year Project / Dissertation / Thesis |
Published: |
2024
|
Subjects: | |
Online Access: | http://eprints.utar.edu.my/6989/1/fyp_CS_2024_NSQ.pdf http://eprints.utar.edu.my/6989/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A review of DDoS attacks and defenses in IoT.
by: Mohd. Sam, Suriani, et al.
Published: (2022) -
Defense against Cache-Based Side Channel Attacks for secure cloud computing
by: Chouhan, M., et al.
Published: (2016) -
A pilot analysis of factors affecting defense against social engineering attacks in the armed forces environment
by: Shahrom, Muhammad Farhan, et al.
Published: (2021) -
Robustness of frequency domain image watermarking against image processing attacks
by: Chai, Jee Sing
Published: (2008) -
A framework for robust deep learning models against adversarial attacks based on a protection layer approach
by: Tan, Shing Chiang, et al.
Published: (2024)