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20162023
most citedExploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval

217 citations · 606 across the 16 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CV2022★ 5 cited

Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection

Xiaonan Lu, Wenhui Diao, Yongqiang Mao +4

Few-shot object detection, expecting detectors to detect novel classes with a few instances, has made conspicuous progress. However, the prototypes extracted by existing meta-learn…

cs.CV2022★ 1 cited

Probabilistic Deep Metric Learning for Hyperspectral Image Classification

Chengkun Wang, Wenzhao Zheng, Xian Sun +2

This paper proposes a probabilistic deep metric learning (PDML) framework for hyperspectral image classification, which aims to predict the category of each pixel for an image capt…

cs.CV2022★ 26 cited

Learning to Evaluate Performance of Multi-modal Semantic Localization

Zhiqiang Yuan, Wenkai Zhang, Chongyang Li +6

Semantic localization (SeLo) refers to the task of obtaining the most relevant locations in large-scale remote sensing (RS) images using semantic information such as text. As an em…

cs.CV2022★ 67 cited

Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification

Yongqiang Mao, Kaiqiang Chen, Wenhui Diao +4

The classification of airborne laser scanning (ALS) point clouds is a critical task of remote sensing and photogrammetry fields. Although recent deep learning-based methods have ac…

cs.CV2022★ 217 cited

Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval

Zhiqiang Yuan, Wenkai Zhang, Kun Fu +4

Remote sensing (RS) cross-modal text-image retrieval has attracted extensive attention for its advantages of flexible input and efficient query. However, traditional methods ignore…