Towards robust visual recognition: learning from imperfect data
Though Deep Convolutional Neural Networks (DCNN) have shown success in many tasks in the field of computer vision, the huge effort made in constructing large-scale annotated datasets is indispensable. Even the prevailing models can fail when the dataset does not cover enough samples. For example, fo...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/164415 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Be the first to leave a comment!