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20172026
most citedDeep learning in remote sensing: a review

3.2k citations · 3.5k across the 39 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023★ 1 cited

A Deep Active Contour Model for Delineating Glacier Calving Fronts

Konrad Heidler, Lichao Mou, Erik Loebel +3

Choosing how to encode a real-world problem as a machine learning task is an important design decision in machine learning. The task of glacier calving front modeling has often bee…

cs.CV2023

RRSIS: Referring Remote Sensing Image Segmentation

Zhenghang Yuan, Lichao Mou, Yuansheng Hua +1

Localizing desired objects from remote sensing images is of great use in practical applications. Referring image segmentation, which aims at segmenting out the objects to which a g…

cs.CV2023

Overcoming Language Bias in Remote Sensing Visual Question Answering via Adversarial Training

Zhenghang Yuan, Lichao Mou, Xiao Xiang Zhu

The Visual Question Answering (VQA) system offers a user-friendly interface and enables human-computer interaction. However, VQA models commonly face the challenge of language bias…

cs.CV2023★ 3 cited

GAMUS: A Geometry-aware Multi-modal Semantic Segmentation Benchmark for Remote Sensing Data

Zhitong Xiong, Sining Chen, Yi Wang +2

Geometric information in the normalized digital surface models (nDSM) is highly correlated with the semantic class of the land cover. Exploiting two modalities (RGB and nDSM (heigh…

cs.CV2023

Multilingual Augmentation for Robust Visual Question Answering in Remote Sensing Images

Zhenghang Yuan, Lichao Mou, Xiao Xiang Zhu

Aiming at answering questions based on the content of remotely sensed images, visual question answering for remote sensing data (RSVQA) has attracted much attention nowadays. Howev…