Sonar image quality evaluation using deep neural network

[1]  Weisi Lin,et al.  Deep Dual-Channel Neural Network for Image-Based Smoke Detection , 2020, IEEE Transactions on Multimedia.

[2]  Chang Wen Chen,et al.  Editorial: On Building a Stronger Multimedia Community , 2016, IEEE Trans. Multim..

[3]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[4]  Jiaying Liu,et al.  Objective Quality Assessment of Screen Content Images by Uncertainty Weighting , 2017, IEEE Transactions on Image Processing.

[5]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[6]  MengChu Zhou,et al.  TL-GDBN: Growing Deep Belief Network With Transfer Learning , 2019, IEEE Transactions on Automation Science and Engineering.

[7]  Weisi Lin,et al.  Saliency-Guided Quality Assessment of Screen Content Images , 2016, IEEE Transactions on Multimedia.

[8]  Yong Liu,et al.  Blind Image Quality Assessment Based on High Order Statistics Aggregation , 2016, IEEE Transactions on Image Processing.

[9]  Jia Zhang,et al.  SGW-SCN: An integrated machine learning approach for workload forecasting in geo-distributed cloud data centers⁎ , 2019, Inf. Sci..

[10]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Yutao Liu,et al.  Blind Image Quality Estimation via Distortion Aggravation , 2018, IEEE Transactions on Broadcasting.

[12]  Ke Gu,et al.  Reference-Free Quality Assessment of Sonar Images via Contour Degradation Measurement , 2019, IEEE Transactions on Image Processing.

[13]  Tian Zhou,et al.  Underwater pipeline leakage detection via multibeam sonar imagery , 2017 .

[14]  Christophe Charrier,et al.  Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain , 2012, IEEE Transactions on Image Processing.

[15]  Alan C. Bovik,et al.  No-Reference Image Quality Assessment in the Spatial Domain , 2012, IEEE Transactions on Image Processing.

[16]  MengChu Zhou,et al.  Time-Dependent Cloud Workload Forecasting via Multi-Task Learning , 2019, IEEE Robotics and Automation Letters.

[17]  Weisi Lin,et al.  Subjective and objective quality evaluation of sonar images for underwater acoustic transmission , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[18]  Wenjun Zhang,et al.  Using Free Energy Principle For Blind Image Quality Assessment , 2015, IEEE Transactions on Multimedia.

[19]  Xiongkuo Min,et al.  Blind Quality Assessment Based on Pseudo-Reference Image , 2018, IEEE Transactions on Multimedia.

[20]  Weisi Lin,et al.  Statistical and Structural Information Backed Full-Reference Quality Measure of Compressed Sonar Images , 2020, IEEE Transactions on Circuits and Systems for Video Technology.

[21]  Weisi Lin,et al.  No-Reference Image Sharpness Assessment in Autoregressive Parameter Space , 2015, IEEE Transactions on Image Processing.

[22]  Lei Zhang,et al.  Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features , 2014, IEEE Transactions on Image Processing.

[23]  Xiongkuo Min,et al.  Partial-Reference Sonar Image Quality Assessment for Underwater Transmission , 2018, IEEE Transactions on Aerospace and Electronic Systems.

[24]  Alan C. Bovik,et al.  Image information and visual quality , 2006, IEEE Trans. Image Process..

[25]  Weisi Lin,et al.  A Fast Reliable Image Quality Predictor by Fusing Micro- and Macro-Structures , 2017, IEEE Transactions on Industrial Electronics.

[26]  Ke Gu,et al.  No-Reference Quality Assessment of Screen Content Pictures , 2017, IEEE Transactions on Image Processing.

[27]  Yoshua Bengio,et al.  Practical Recommendations for Gradient-Based Training of Deep Architectures , 2012, Neural Networks: Tricks of the Trade.

[28]  Weisi Lin,et al.  Learning a blind quality evaluation engine of screen content images , 2016, Neurocomputing.