39 citations · 40 across the 8 of their papers we have counts for
9 papers
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…
Confidence-Guided Semi-supervised Learning in Land Cover Classification
Wanli Ma, Oktay Karakus, Paul L. Rosin
Semi-supervised learning has been well developed to help reduce the cost of manual labelling by exploiting a large quantity of unlabelled data. Especially in the application of lan…
High-precision Density Mapping of Marine Debris and Floating Plastics via Satellite Imagery
Henry Booth, Wanli Ma, Oktay Karakus
Combining multi-spectral satellite data and machine learning has been suggested as a method for monitoring plastic pollutants in the ocean environment. Recent studies have made the…
Reinforcement Learning based Voice Interaction to Clear Path for Robots in Elevator Environment
Wanli Ma, Xinyi Gao, Jianwei Shi +4
Efficient use of the space in an elevator is very necessary for a service robot, due to the need for reducing the amount of time caused by waiting for the next elevator. To provide…