An Effective Receptive Field-Guided Parallel Resolution ConvNet for Underwater Salient Object Detection

Abstract

Underwater salient object detection is complicated by image degradation and large object-scale variation. This paper proposes an effective receptive field-guided parallel-resolution ConvNet to combine receptive-field control with multiresolution representation, improving detection of salient underwater objects in challenging visual scenes.

Shaojian Yang

Assistant Research Fellow / Postdoctoral Fellow

My research interests include underwater communications, distributed acoustic sensing and ocean Internet of Things.