scholarly journals NorFisk: fish image dataset from Norwegian fish farms for species recognition using deep neural networks

2021 ◽  
Vol 42 (1) ◽  
pp. 1-16
Author(s):  
Alberto Maximiliano Crescitelli ◽  
Lars Christian Gansel ◽  
Houxiang Zhang
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Species Recognition ◽  
Fish Farms ◽  
Image Dataset

scholarly journals Effect of levels in Dual Tree Complex Wavelet Transform when design Universal image stego-analytic

2020 ◽  
pp. 665-674
Author(s):  
Hana Mohsen ◽  
Halah Hasan
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Deep Neural Networks ◽  
Adaptive Methods ◽  
Natural Images ◽  
Detection Accuracy ◽  
Complex Wavelet Transform ◽  
Image Dataset ◽  
Complex Wavelet ◽  
Content Adaptive

Universal image stego-analytic has become an important issue due to the natural images features curse of dimensionality. Deep neural networks, especially deep convolution networks, have been widely used for the problem of universal image stegoanalytic design. This paper describes the effect of selecting suitable value for number of levels during image pre-processing with Dual Tree Complex Wavelet Transform. This value may significantly affect the detection accuracy which is obtained to evaluate the performance of the proposed system. The proposed system is evaluated using three content-adaptive methods, named Highly Undetetable steGO (HUGO), Wavelet Obtained Weights (WOW) and UNIversal WAvelet Relative Distortion (UNIWARD).The obtained precision 0.98387, 0.96659 and 0.98387 for the three content-adaptive methods, applied on BOSS image dataset, respectively. The obtained results show that number of level equals to 5 outperforms other numbers in terms of detection accuracy. Also it minimizes the ime required for both training and testing phases.

Deep neural networks trained with heavier data augmentation learn features closer to representations in hIT

2018 ◽  
Author(s):  
Alex Hernández-García ◽  
Johannes Mehrer ◽  
Nikolaus Kriegeskorte ◽  
Peter König ◽  
Tim C. Kietzmann
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Data Augmentation

Representation of adversarial images in deep neural networks and the human brain

2018 ◽  
Author(s):  
Chi Zhang ◽  
Xiaohan Duan ◽  
Ruyuan Zhang ◽  
Li Tong
Keyword(s):  
Neural Networks ◽  
Human Brain ◽  
Deep Neural Networks

Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks

2018 ◽  
Author(s):  
Daniel Povey ◽  
Gaofeng Cheng ◽  
Yiming Wang ◽  
Ke Li ◽  
Hainan Xu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Matrix Factorization ◽  
Deep Neural Networks ◽  
Low Rank ◽  
Rank Matrix ◽  
Low Rank Matrix
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