Improved salient object detection using hybrid Convolution Recurrent Neural Network

2021 ◽  
Vol 166 ◽  
pp. 114064
Author(s):  
NalliyannaV. Kousik ◽  
Yuvaraj Natarajan ◽  
R. Arshath Raja ◽  
Suresh Kallam ◽  
Rizwan Patan ◽  
...  
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Recurrent Neural Network ◽  
Salient Object Detection ◽  
Salient Object

Edge-Aware Convolution Neural Network Based Salient Object Detection

2019 ◽  
Vol 26 (1) ◽  
pp. 114-118 ◽  
Author(s):  
Wenlong Guan ◽  
Tiantian Wang ◽  
Jinqing Qi ◽  
Lihe Zhang ◽  
Huchuan Lu
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Salient Object Detection ◽  
Convolution Neural Network ◽  
Salient Object

MFC-Net : Multi-feature fusion cross neural network for salient object detection

2021 ◽  
pp. 104243
Author(s):  
Zhenyu Wang ◽  
Yunzhou Zhang ◽  
Yan Liu ◽  
Shichang Liu ◽  
Sonya Coleman ◽  
...  
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Feature Fusion ◽  
Salient Object Detection ◽  
Salient Object

SuperCNN: A Superpixelwise Convolutional Neural Network for Salient Object Detection

2015 ◽  
Vol 115 (3) ◽  
pp. 330-344 ◽  
Author(s):  
Shengfeng He ◽  
Rynson W. H. Lau ◽  
Wenxi Liu ◽  
Zhe Huang ◽  
Qingxiong Yang
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Convolutional Neural Network ◽  
Salient Object Detection ◽  
Salient Object

Salient object detection for RGB-D image by single stream recurrent convolution neural network

2019 ◽  
Vol 363 ◽  
pp. 46-57 ◽  
Author(s):  
Zhengyi Liu ◽  
Song Shi ◽  
Quntao Duan ◽  
Wei Zhang ◽  
Peng Zhao
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Salient Object Detection ◽  
Convolution Neural Network ◽  
Salient Object ◽  
Single Stream

scholarly journals DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection

2016 ◽  
Vol 25 (8) ◽  
pp. 3919-3930 ◽  
Author(s):  
Xi Li ◽  
Liming Zhao ◽  
Lina Wei ◽  
Ming-Hsuan Yang ◽  
Fei Wu ◽  
...  
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Network Model ◽  
Neural Network Model ◽  
Deep Neural Network ◽  
Salient Object Detection ◽  
Salient Object

Deep quaternion fourier transform for salient object detection

2021 ◽  
pp. 1-10
Author(s):  
T. Revathi ◽  
T.M. Rajalaxmi ◽  
R. Sundara Rajan ◽  
Wilhelm Passarella Freire
Keyword(s):  
Neural Network ◽  
Fourier Transform ◽  
Object Detection ◽  
Deep Neural Network ◽  
Salient Object Detection ◽  
Learning System ◽  
Computational Time ◽  
Fourier Domain ◽  
Salient Object ◽  
Quaternion Fourier Transform

Salient object detection plays a vital role in image processing applications like image retrieval, security and surveillance in authentic-time. In recent times, advances in deep neural network gained more attention in the automatic learning system for various computer vision applications. In order to decrement the detection error for efficacious object detection, we proposed a detection classifier to detect the features of the object utilizing a deep neural network called convolutional neural network (CNN) and discrete quaternion Fourier transform (DQFT). Prior to CNN, the image is pre-processed by DQFT in order to handle all the three colors holistically to evade loss of image information, which in-turn increase the effective use of object detection. The features of the image are learned by training model of CNN, where the CNN process is done in the Fourier domain to quicken the method in productive computational time, and the image is converted to spatial domain before processing the fully connected layer. The proposed model is implemented in the HDA and INRIA benchmark datasets. The outcome shows that convolution in the quaternion Fourier domain expedite the process of evaluation with amended detection rate. The comparative study is done with CNN, discrete Fourier transforms CNN, RNN ad masked RNN.

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