안녕, 세상!

Abstract EPSANet Novel lightweight and effective attention method Replacing the 3x3 convolution with the PSA module in the bottleneck blocks of the ResNet Be developed by stacking ResNet-style EPSA blocks Strong multi-scale representation ability for various computer vision tasks Outperforming most of the state-of-the-art channel attention methods Introduction Specifically two types of attention..

Abstract For underwater image classification Simulate the visual correlation of background attention with image understanding for special environments, such as fog and underwater by I-A module I-A moudule : Inception-Attention module Introduction Underwater image : Complex distortions (low contrast, blurring, non-uniform brightness...) Three key points 1) 서로 다른 환경들에서 찍힌 underwater images의 backgr..