258 citations · 538 across the 39 of their papers we have counts for
11 papers · 1 filter
Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty
Katharina Hechinger, Christoph Koller, Xiao Xiang Zhu +1
Uncertainty in machine learning models is a timely and vast field of research. In supervised learning, uncertainty can already occur in the first stage of the training process, the…
Categorising the World into Local Climate Zones -- Towards Quantifying Labelling Uncertainty for Machine Learning Models
Katharina Hechinger, Xiao Xiang Zhu, Göran Kauermann
Image classification is often prone to labelling uncertainty. To generate suitable training data, images are labelled according to evaluations of human experts. This can result in…
Deep Semantic Model Fusion for Ancient Agricultural Terrace Detection
Yi Wang, Chenying Liu, Arti Tiwari +4
Discovering ancient agricultural terraces in desert regions is important for the monitoring of long-term climate changes on the Earth's surface. However, traditional ground surveys…
Semi-Supervised Learning for hyperspectral images by non parametrically predicting view assignment
Shivam Pande, Nassim Ait Ali Braham, Yi Wang +3
Hyperspectral image (HSI) classification is gaining a lot of momentum in present time because of high inherent spectral information within the images. However, these images suffer…
DisasterNets: Embedding Machine Learning in Disaster Mapping
Qingsong Xu, Yilei Shi, Xiao Xiang Zhu
Disaster mapping is a critical task that often requires on-site experts and is time-consuming. To address this, a comprehensive framework is presented for fast and accurate recogni…
The Politics of Language Choice: How the Russian-Ukrainian War Influences Ukrainians' Language Use on Twitter
Daniel Racek, Brittany I. Davidson, Paul W. Thurner +2
The use of language is innately political and often a vehicle of cultural identity as well as the basis for nation building. Here, we examine language choice and tweeting activity…
Overcoming Language Bias in Remote Sensing Visual Question Answering via Adversarial Training
Zhenghang Yuan, Lichao Mou, Xiao Xiang Zhu
The Visual Question Answering (VQA) system offers a user-friendly interface and enables human-computer interaction. However, VQA models commonly face the challenge of language bias…
GAMUS: A Geometry-aware Multi-modal Semantic Segmentation Benchmark for Remote Sensing Data
Zhitong Xiong, Sining Chen, Yi Wang +2
Geometric information in the normalized digital surface models (nDSM) is highly correlated with the semantic class of the land cover. Exploiting two modalities (RGB and nDSM (heigh…
Biomass Estimation and Uncertainty Quantification from Tree Height
Qian Song, Conrad M Albrecht, Zhitong Xiong +1
We propose a tree-level biomass estimation model approximating allometric equations by LiDAR data. Since tree crown diameters estimation is challenging from spaceborne LiDAR measur…
Multilingual Augmentation for Robust Visual Question Answering in Remote Sensing Images
Zhenghang Yuan, Lichao Mou, Xiao Xiang Zhu
Aiming at answering questions based on the content of remotely sensed images, visual question answering for remote sensing data (RSVQA) has attracted much attention nowadays. Howev…
Universal Domain Adaptation for Remote Sensing Image Scene Classification
Qingsong Xu, Yilei Shi, Xin Yuan +1
The domain adaptation (DA) approaches available to date are usually not well suited for practical DA scenarios of remote sensing image classification, since these methods (such as…