TY - GEN
T1 - A Scale-Reductive Pooling with Majority-Take-All for Salient Object Detection
AU - Shen, Chin Han
AU - Chen, Yang Jie
AU - Hsiao, Hsu Feng
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the rapid development of hardware and related technologies, salient object detection based on deep learning methods has become one of the popular research topics in computer vision applications. For the detection focused on the integrity of salient objects, edge accuracy of objects is one of the important indicators in the evaluation of visual saliency detection. However, in deep learning-based methods, complex networks and large amounts of data are usually required to achieve good boundary accuracy. To solve this issue, a scale-reductive pooling approach with clustering-based majority-take-all strategy is proposed in this paper. According to the experimental results, we show that the prediction results are improved with reasonable quantity of superpixels.
AB - With the rapid development of hardware and related technologies, salient object detection based on deep learning methods has become one of the popular research topics in computer vision applications. For the detection focused on the integrity of salient objects, edge accuracy of objects is one of the important indicators in the evaluation of visual saliency detection. However, in deep learning-based methods, complex networks and large amounts of data are usually required to achieve good boundary accuracy. To solve this issue, a scale-reductive pooling approach with clustering-based majority-take-all strategy is proposed in this paper. According to the experimental results, we show that the prediction results are improved with reasonable quantity of superpixels.
KW - deep learning
KW - salient object detection
KW - superpixel pooling
UR - http://www.scopus.com/inward/record.url?scp=85142488613&partnerID=8YFLogxK
U2 - 10.1109/ISCAS48785.2022.9937485
DO - 10.1109/ISCAS48785.2022.9937485
M3 - Conference contribution
AN - SCOPUS:85142488613
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 3309
EP - 3313
BT - IEEE International Symposium on Circuits and Systems, ISCAS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022
Y2 - 27 May 2022 through 1 June 2022
ER -