Deep neural network compression for pixel-level vision tasks
Deep convolutional neural networks (DCNNs) have demonstrated remarkable performance in many computer vision tasks. In order to achieve this, DCNNs typically require a large number of trainable parameters that are optimized to extract informative features. This often results in over-parameterization...
Saved in:
Main Author: | He, Wei |
---|---|
Other Authors: | Lam Siew Kei |
Format: | Thesis-Master by Research |
Language: | English |
Published: |
Nanyang Technological University
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/150076 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Deep neural network compression : from sufficient to scarce data
by: Chen, Shangyu
Published: (2021) -
Hybrid deep neural network and deep reinforcement learning for algorithmic finance
by: Ooi, Min Hui
Published: (2022) -
Deep neural networks for time series classification
by: Cheng, Wen Xin
Published: (2023) -
Using deep neural networks for chess position evaluation
by: Phang, Benito Yan Feng
Published: (2023) -
Deep GRU neural networks for gold price prediction
by: Kuan, Soon Yee
Published: (2023)