Search Results for author: Mark Mulligan

Found 3 papers, 2 papers with code

AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a Single High-Resolution Image

no code implementations5 Feb 2024 Hamed Amini Amirkolaee, Miaojing Shi, Lianghua He, Mark Mulligan

For the latter, an attention-to-adapt mechanism is introduced to distill relevant information from different domains while generating tree density maps; a hierarchical cross-domain feature alignment scheme is proposed that progressively aligns the features from the source and target domains.

Domain Adaptation

TreeFormer: a Semi-Supervised Transformer-based Framework for Tree Counting from a Single High Resolution Image

1 code implementation12 Jul 2023 Hamed Amini Amirkolaee, Miaojing Shi, Mark Mulligan

Automatic tree density estimation and counting using single aerial and satellite images is a challenging task in photogrammetry and remote sensing, yet has an important role in forest management.

Density Estimation

Dam reservoir extraction from remote sensing imagery using tailored metric learning strategies

1 code implementation12 Jul 2022 Arnout van Soesbergen, Zedong Chu, Miaojing Shi, Mark Mulligan

Extensive experiments were conducted on this benchmark in the water body segmentation task, dam reservoir recognition task, and the joint dam reservoir extraction task.

Metric Learning Segmentation

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