most citedEarly- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach

9 citations · 10 across the 4 of their papers we have counts for

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cs.CV20219 cited

Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach

Chenxi Lin, Liheng Zhong, Xiao-Peng Song +3

Land cover classification in remote sensing is often faced with the challenge of limited ground truth. Incorporating historical information has the potential to significantly lower…

cs.CV2021

Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping

Rahul Ghosh, Xiaowei Jia, Chenxi Lin +2

Collecting large annotated datasets in Remote Sensing is often expensive and thus can become a major obstacle for training advanced machine learning models. Common techniques of ad…

cs.CV2021

Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping

Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia +3

The availability of massive earth observing satellite data provide huge opportunities for land use and land cover mapping. However, such mapping effort is challenging due to the ex…

cs.CV2021

Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement

Lijun Gou, Shengkai Wu, Jinrong Yang +4

One major impediment in rapidly deploying object detection models for industrial applications is the lack of large annotated datasets. We currently have presented the Sacked Carton…

cs.CV20211 cited

SCD: A Stacked Carton Dataset for Detection and Segmentation

Jinrong Yang, Shengkai Wu, Lijun Gou +5

Carton detection is an important technique in the automatic logistics system and can be applied to many applications such as the stacking and unstacking of cartons, the unloading o…