Search Results for author:
Found 16 papers, 4 papers with code
A Graph-Matching Approach for Cross-view Registration of Over-view 2 and Street-view based Point Clouds
In this paper, based on the assumption that the object boundaries (e. g., buildings) from the over-view data should coincide with footprints of fa\c{c}ade 3D points generated from street-view photogrammetric images, we aim to address this problem by proposing a fully automated geo-registration method for cross-view data, which utilizes semantically segmented object boundaries as view-invariant features under a global optimization framework through graph-matching: taking the over-view point clouds generated from stereo/multi-stereo satellite images and the street-view point clouds generated from monocular video images as the inputs, the proposed method models segments of buildings as nodes of graphs, both detected from the satellite-based and street-view based point clouds, thus to form the registration as a graph-matching problem to allow non-rigid matches; to enable a robust solution and fully utilize the topological relations between these segments, we propose to address the graph-matching problem on its conjugate graph solved through a belief-propagation algorithm.
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text
Named entity disambiguation (NED), which involves mapping textual mentions to structured entities, is particularly challenging in the medical domain due to the presence of rare entities.
Graph-based Incident Aggregation for Large-Scale Online Service Systems
The proposed framework is evaluated with real-world incident data collected from a large-scale online service system of Huawei Cloud.
Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems
The industrial machine learning pipeline requires iterating on model features, training and deploying models, and monitoring deployed models at scale.
A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse
In this paper, we present a case study that performs an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition event.
A Unified Framework of Bundle Adjustment and Feature Matching for High-Resolution Satellite Images
Bundle adjustment (BA) is a technique for refining sensor orientations of satellite images, while adjustment accuracy is correlated with feature matching results.
3D Reconstruction through Fusion of Cross-View Images
3D recovery from multi-stereo and stereo images, as an important application of the image-based perspective geometry, serves many applications in computer vision, remote sensing and Geomatics.
Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP
These experiments on AmbER sets show their utility as an evaluation tool and highlight the weaknesses of popular retrieval systems.
Hierarchical Disentangled Representation Learning for Outdoor Illumination Estimation and Editing
However, naively compressing an outdoor panorama into a low-dimensional latent vector, as existing models have done, causes two major problems.
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
A challenge for named entity disambiguation (NED), the task of mapping textual mentions to entities in a knowledge base, is how to disambiguate entities that appear rarely in the training data, termed tail entities.
Ranked #1 on
Entity Disambiguation
on AIDA-CoNLL
(Micro-F1 metric)
How Different is Test Case Prioritization for Open and Closed Source Projects?
Improved test case prioritization means that software developers can detect and fix more software faults sooner than usual.
Software Engineering
Improving Knowledge Base Construction from Robust Infobox Extraction
One important approach to constructing a comprehensive knowledge base is to extract information from Wikipedia infobox tables to populate an existing KB.
Recurrent Attention Unit
In this paper, we propose a RNN model, called Recurrent Attention Unit (RAU), which seamlessly integrates the attention mechanism into the interior of GRU by adding an attention gate.
Learning Translations via Matrix Completion
Bilingual Lexicon Induction is the task of learning word translations without bilingual parallel corpora.
Design Challenges for Entity Linking
Recent research on entity linking (EL) has introduced a plethora of promising techniques, ranging from deep neural networks to joint inference.
