TY - JOUR
T1 - Salient object detection
T2 - a mini review
AU - Wang, Xiuwenxin
AU - Yu, Siyue
AU - Lim, Eng Gee
AU - Wong, M. L.Dennis
N1 - Publisher Copyright:
Copyright © 2024 Wang, Yu, Lim and Wong.
PY - 2024
Y1 - 2024
N2 - This paper presents a mini-review of recent works in Salient Object Detection (SOD). First, We introduce SOD and its application in image processing tasks and applications. Following this, we discuss the conventional methods for SOD and present several recent works in this category. With the start of deep learning AI algorithms, SOD has also benefited from deep learning. Here, we present and discuss Deep learning-based SOD according to its training mechanism, i.e., fully supervised and weakly supervised. For the benefit of the readers, we have also included some standard data sets assembled for SOD research.
AB - This paper presents a mini-review of recent works in Salient Object Detection (SOD). First, We introduce SOD and its application in image processing tasks and applications. Following this, we discuss the conventional methods for SOD and present several recent works in this category. With the start of deep learning AI algorithms, SOD has also benefited from deep learning. Here, we present and discuss Deep learning-based SOD according to its training mechanism, i.e., fully supervised and weakly supervised. For the benefit of the readers, we have also included some standard data sets assembled for SOD research.
KW - computer vision
KW - conventional salient object detection
KW - deep learning
KW - mini review
KW - salient object detection
UR - http://www.scopus.com/inward/record.url?scp=85204806397&partnerID=8YFLogxK
U2 - 10.3389/frsip.2024.1356793
DO - 10.3389/frsip.2024.1356793
M3 - Short survey
AN - SCOPUS:85204806397
SN - 2673-8198
VL - 4
JO - Frontiers in Signal Processing
JF - Frontiers in Signal Processing
M1 - 1356793
ER -