Search Results for author: Yu Hao

Found 19 papers, 3 papers with code

Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data

1 code implementation6 Oct 2022 Yu Hao, Hiroyuki Kasahara

We apply our EM test to estimate the number of production technology types for the finite mixture Cobb-Douglas production function model studied by Kasahara et al. (2022) used the panel data of the Japanese and Chilean manufacturing firms.


Understanding the Impact of Image Quality and Distance of Objects to Object Detection Performance

no code implementations17 Sep 2022 Yu Hao, Haoyang Pei, Yixuan Lyu, Zhongzheng Yuan, John-Ross Rizzo, Yao Wang, Yi Fang

We further assess the impact of the distance of an object to the camera on the detection accuracy and show that higher spatial resolution enables a greater detection range.

object-detection Object Detection

Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision

no code implementations17 Aug 2022 Yu Hao, Junchi Feng, John-Ross Rizzo, Yao Wang, Yi Fang

These functions enable the system to suggest an initial navigation path, continuously update the path as the user moves, and offer timely recommendation about the correction of the user's path.

Object Localization

Runner-Up Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: Cropped Word Recognition

no code implementations4 Aug 2022 Zhangzi Zhu, Yu Hao, Wenqing Zhang, Chuhui Xue, Song Bai

This report presents our 2nd place solution to ECCV 2022 challenge on Out-of-Vocabulary Scene Text Understanding (OOV-ST) : Cropped Word Recognition.

Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detection and Spotting

no code implementations8 Mar 2022 Chuhui Xue, Wenqing Zhang, Yu Hao, Shijian Lu, Philip Torr, Song Bai

Our network consists of an image encoder and a character-aware text encoder that extract visual and textual features, respectively, as well as a visual-textual decoder that models the interaction among textual and visual features for learning effective scene text representations.

Optical Character Recognition (OCR) Scene Text Detection

Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to "See" More, Farther and Faster

no code implementations25 Dec 2021 Zhongzheng Yuan, Tommy Azzino, Yu Hao, Yixuan Lyu, Haoyang Pei, Alain Boldini, Marco Mezzavilla, Mahya Beheshti, Maurizio Porfiri, Todd Hudson, William Seiple, Yi Fang, Sundeep Rangan, Yao Wang, J. R. Rizzo

The vision evaluation is combined with a detailed full-stack wireless network simulation to determine the distribution of throughputs and delays with real navigation paths and ray-tracing from new high-resolution 3D models in an urban environment.

Edge-computing object-detection +1

KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural Network

no code implementations NeurIPS 2021 Yu Hao, Xin Cao, Yufan Sheng, Yixiang Fang, Wei Wang

Keyword search is a fundamental task to retrieve information that is the most relevant to the query keywords.

3D Meta-Segmentation Neural Network

no code implementations8 Oct 2021 Yu Hao, Yi Fang

Based on the learned information of task distribution, our meta part segmentation learner is able to dynamically update the part segmentation learner with optimal parameters which enable our part segmentation learner to rapidly adapt and have great generalization ability on new part segmentation tasks.

3D Part Segmentation Meta-Learning

Meta-Learning 3D Shape Segmentation Functions

no code implementations8 Oct 2021 Yu Hao, Yi Fang

We show in experiments that our meta-learning approach, denoted as Meta-3DSeg, leads to improvements on unsupervised 3D shape segmentation over the conventional designs of deep neural networks for 3D shape segmentation functions.

3D Shape Reconstruction Meta-Learning

RAR: Region-Aware Point Cloud Registration

no code implementations7 Oct 2021 Yu Hao, Yi Fang

More specifically, we develop a novel region-aware decoder (RAD) module that is formed with an implicit neural region representation parameterized by neural networks.

3D Shape Reconstruction Point Cloud Registration +1

3D Meta-Registration: Meta-learning 3D Point Cloud Registration Functions

no code implementations29 Sep 2021 Yu Hao, Yi Fang

Learning robust 3D point cloud registration functions with deep neural networks has emerged as a powerful paradigm in recent years, offering promising performance in producing spatial geometric transformations for each pair of 3D point clouds.

Meta-Learning Point Cloud Registration

3D Meta-Registration: Learning to Learn Registration of 3D Point Clouds

no code implementations22 Oct 2020 Lingjing Wang, Yu Hao, Xiang Li, Yi Fang

In this paper, we propose a meta-learning based 3D registration model, named 3D Meta-Registration, that is capable of rapidly adapting and well generalizing to new 3D registration tasks for unseen 3D point clouds.

Meta-Learning Point Cloud Registration

Inductive Link Prediction for Nodes Having Only Attribute Information

1 code implementation16 Jul 2020 Yu Hao, Xin Cao, Yixiang Fang, Xike Xie, Sibo Wang

In attributed graphs, both the structure and attribute information can be utilized for link prediction.

Inductive Link Prediction

Exploiting Sentence Embedding for Medical Question Answering

no code implementations15 Nov 2018 Yu Hao, Xien Liu, Ji Wu, Ping Lv

The learning framework consists of two main parts: 1) a sentence embedding producing module, and 2) a scoring module.

Association Question Answering +2

TransA: An Adaptive Approach for Knowledge Graph Embedding

no code implementations18 Sep 2015 Han Xiao, Minlie Huang, Yu Hao, Xiaoyan Zhu

Knowledge representation is a major topic in AI, and many studies attempt to represent entities and relations of knowledge base in a continuous vector space.

Knowledge Graph Embedding Metric Learning +1

TransG : A Generative Mixture Model for Knowledge Graph Embedding

no code implementations18 Sep 2015 Han Xiao, Minlie Huang, Yu Hao, Xiaoyan Zhu

Recently, knowledge graph embedding, which projects symbolic entities and relations into continuous vector space, has become a new, hot topic in artificial intelligence.

Knowledge Graph Embedding

Knowlege Graph Embedding by Flexible Translation

no code implementations20 May 2015 Jun Feng, Mantong Zhou, Yu Hao, Minlie Huang, Xiaoyan Zhu

TransF regards relation as translation between head entity vector and tail entity vector with flexible magnitude.

General Classification Knowledge Graph Embedding +3

Cannot find the paper you are looking for? You can Submit a new open access paper.