Improved salient object detection using hybrid Convolution Recurrent Neural Network

N.V. Kousik; N. Yuvaraj; R. Arshath Raja; Suresh Kallam; Rizwan Patan; Amir H. Gandomi

doi:10.1016/j.eswa.2020.114064

ScienceGate Book Chapters

JOURNAL ARTICLE

Improved salient object detection using hybrid Convolution Recurrent Neural Network

N.V. Kousik N. Yuvaraj R. Arshath Raja Suresh Kallam Rizwan Patan Amir H. Gandomi

Year: 2020 Journal: Expert Systems with Applications Vol: 166 Pages: 114064-114064 Publisher: Elsevier BV

DOI: 10.1016/j.eswa.2020.114064

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Benchmark (surveying) Artificial intelligence Recurrent neural network Convolution (computer science) Convolutional neural network Object detection Pattern recognition (psychology) Deep learning Computer vision Object (grammar) Constraint (computer-aided design) Artificial neural network

Metrics

122

Cited By

7.35

FWCI (Field Weighted Citation Impact)

Refs

0.98

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Visual Attention and Saliency Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Video Quality Assessment

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Improved salient object detection using hybrid Convolution Recurrent Neural Network

Metrics

Citation History

Topics

Related Documents

Edge-Aware Convolution Neural Network Based Salient Object Detection

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

Lung Cancer Detection Using Hybrid Convolution neural Network and Recurrent neural Network

An Improved Convolution Neural Network for Object Detection Using YOLOv2

Image salient object detection with refined deep features via convolution neural network