1 citations · 1 across the 4 of their papers we have counts for
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Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation
Wanli Ma, Jiangwen Lu, Qinmu Peng +1
Training-free open-vocabulary semantic segmentation (OVSS) partitions an image into semantically distinct regions based on arbitrary text descriptions, without learning any additio…
Core-Set Selection for Data-efficient Land Cover Segmentation
Keiller Nogueira, Akram Zaytar, Wanli Ma +9
The increasing accessibility of remotely sensed data and their potential to support large-scale decision-making have driven the development of deep learning models for many Earth O…
Patch-GAN Transfer Learning with Reconstructive Models for Cloud Removal
Wanli Ma, Oktay Karakus, Paul L. Rosin
Cloud removal plays a crucial role in enhancing remote sensing image analysis, yet accurately reconstructing cloud-obscured regions remains a significant challenge. Recent advancem…
Integrating Semi-Supervised and Active Learning for Semantic Segmentation
Wanli Ma, Oktay Karakus, Paul L. Rosin
In this paper, we propose a novel active learning approach integrated with an improved semi-supervised learning framework to reduce the cost of manual annotation and enhance model…
Knowledge Distillation for Road Detection based on cross-model Semi-Supervised Learning
Wanli Ma, Oktay Karakus, Paul L. Rosin
The advancement of knowledge distillation has played a crucial role in enabling the transfer of knowledge from larger teacher models to smaller and more efficient student models, a…
DiverseNet: Decision Diversified Semi-supervised Semantic Segmentation Networks for Remote Sensing Imagery
Wanli Ma, Oktay Karakus, Paul L. Rosin
Semi-supervised learning (SSL) aims to help reduce the cost of the manual labelling process by leveraging a substantial pool of unlabelled data alongside a limited set of labelled…