no code implementations • 14 Feb 2024 • Chenxi Lin, Jiayu Ren, Guoxiu He, Zhuoren Jiang, Haiyan Yu, Xiaomin Zhu
Moreover, TEAROOM comprises a self-motivation strategy for another LLM equipped with a trainable adapter and a linear layer.
no code implementations • 1 Jan 2023 • Leikun Yin, Rahul Ghosh, Chenxi Lin, David Hale, Christoph Weigl, James Obarowski, Junxiong Zhou, Jessica Till, Xiaowei Jia, Troy Mao, Vipin Kumar, Zhenong Jin
In particular, we developed a SpatioTemporal Classification with Attention (STCA) model to map the distribution of cashew plantations, which can fully capture texture information from discriminative time steps during a growing season.
no code implementations • 19 Oct 2021 • Chenxi Lin, Liheng Zhong, Xiao-Peng Song, Jinwei Dong, David B. Lobell, Zhenong Jin
Land cover classification in remote sensing is often faced with the challenge of limited ground truth.
no code implementations • 16 Aug 2021 • Rahul Ghosh, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar
Common techniques of addressing this issue, based on the underlying idea of pre-training the Deep Neural Networks (DNN) on freely available large datasets, cannot be used for Remote Sensing due to the unavailability of such large-scale labeled datasets and the heterogeneity of data sources caused by the varying spatial and spectral resolution of different sensors.
no code implementations • 2 May 2021 • Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar
The availability of massive earth observing satellite data provide huge opportunities for land use and land cover mapping.
1 code implementation • 19 Mar 2021 • Lijun Gou, Shengkai Wu, Jinrong Yang, Hangcheng Yu, Chenxi Lin, Xiaoping Li, Chao Deng
To solve this problem, a novel image synthesis method is proposed to replace the foreground texture of the source datasets with the texture of the target datasets.
1 code implementation • 25 Feb 2021 • Jinrong Yang, Shengkai Wu, Lijun Gou, Hangcheng Yu, Chenxi Lin, Jiazhuo Wang, Minxuan Li, Xiaoping Li
In this paper, we present a large-scale carton dataset named Stacked Carton Dataset(SCD) with the goal of advancing the state-of-the-art in carton detection.