http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Flood Video Segmentation on Remotely Sensed UAV Using Improved Efficient Neural Network
Naili Suri Inthizami,M. Anwar Ma’sum,Machmud R. Alhamidi,Ahmad Gamal,Ronni Ardhianto,Kurnianingsih,Wisnu Jatmiko 한국통신학회 2022 ICT Express Vol.8 No.3
Semantic segmentation can be used to analyze the video data taken by UAV in the flood monitoring system. An accurate analysis can help rescue teams to assess and mitigate flood disasters. This paper proposed an improved Efficient Neural Network architecture to segment the UAV video of flood disaster. The proposed method consists of atrous separable convolution as the encoder and depth-wise separable convolution as the decoder. The experimental results reveal that the proposed method outperforms Efficient Neural Networks’ other architecture and gives the highest frame per second.