Performance analysis of convolutional neural networks extended with predefined kernels in image classification / Arash Fatehi
While Machine Learning aims to solve more challenging problems, Artificial Neural Networks (ANN) become deeper and more accurate. Convolutional Neural Network (CNN) is not an exception and state-of-art architectures consist of millions of learnable parameters. Aiming for better performance, these ne...
Saved in:
Main Author: | Arash , Fatehi |
---|---|
Format: | Thesis |
Published: |
2022
|
Subjects: | |
Online Access: | http://studentsrepo.um.edu.my/14682/1/Arash_Fatehi.pdf http://studentsrepo.um.edu.my/14682/2/Arash_Fatehi.pdf http://studentsrepo.um.edu.my/14682/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predefined Object Reduction
by: Mohammed, Mohammed Adam Taheir, et al.
Published: (2013) -
Convolutional neural network long short-term memory (CNN + LSTM) for histopathology cancer image classification
by: Zainudin, Zanariah, et al.
Published: (2020) -
Development of hybrid convolutional neural network and autoregressive integrated moving average on computed tomography image classification
by: Abdulrazak Yahya, Saleh, et al.
Published: (2023) -
Applicability and usability of predefined natural language boilerplates in documenting requirements
by: Ibrahim, N., et al.
Published: (2015) -
A convolution neural network-based seed classification system
by: Gulzar, Yonis, et al.
Published: (2020)