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
Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2498
Author(s):  
Tamino Huxohl ◽  
Franz Kummert

In this work, the creation of a dataset labeled in a pixel-wise manner for the uncommon domain of stain detection on patterned laundry is described. The unique properties of images in this dataset—stains are small and sometimes occur in large amounts—led to the creation of noisy labels. Indeed, the training of a fully convolutional neural network for salient object detection with this dataset revealed that the model predicts stains missed by human labelers. Thus, the reduction in label noise by adding overlooked regions with the help of the model’s predictions is examined in two different experiments. In the model-assisted labeling experiment, a simulation is ran where a human selects correct regions from the predictions. In the self-training experiment, regions of high certainty are automatically selected from the predictions. Re-training the model with the revised labels shows that model-assisted labeling leads to an average improvement in performance by 8.52%. In contrast, with self-training, the performance increase is generally lower (2.58% on average) and a decrease is even possible since regions of high certainty are often false positives.


2019 ◽  
Vol 26 (1) ◽  
pp. 114-118 ◽  
Author(s):  
Wenlong Guan ◽  
Tiantian Wang ◽  
Jinqing Qi ◽  
Lihe Zhang ◽  
Huchuan Lu

2021 ◽  
pp. 104243
Author(s):  
Zhenyu Wang ◽  
Yunzhou Zhang ◽  
Yan Liu ◽  
Shichang Liu ◽  
Sonya Coleman ◽  
...  

2019 ◽  
Vol 363 ◽  
pp. 46-57 ◽  
Author(s):  
Zhengyi Liu ◽  
Song Shi ◽  
Quntao Duan ◽  
Wei Zhang ◽  
Peng Zhao

2021 ◽  
Vol 166 ◽  
pp. 114064
Author(s):  
NalliyannaV. Kousik ◽  
Yuvaraj Natarajan ◽  
R. Arshath Raja ◽  
Suresh Kallam ◽  
Rizwan Patan ◽  
...  

2016 ◽  
Vol 25 (8) ◽  
pp. 3919-3930 ◽  
Author(s):  
Xi Li ◽  
Liming Zhao ◽  
Lina Wei ◽  
Ming-Hsuan Yang ◽  
Fei Wu ◽  
...  

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