Match!
Fei-Yue Wang
Chinese Academy of Sciences
Machine learningEngineeringComputer scienceSimulationIntelligent transportation system
652Publications
53H-index
13.2kCitations
What is this?
Publications 628
Newest
Source
Jul 11, 2020 in IJCAI (International Joint Conference on Artificial Intelligence)
#2Lan Yan (CAS: Chinese Academy of Sciences)H-Index: 1
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 4 authors...
#1Xiujuan Wang (CAS: Chinese Academy of Sciences)H-Index: 3
#2Mengzhen Kang (CAS: Chinese Academy of Sciences)H-Index: 12
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 8 authors...
Abstract To elucidate the mechanisms underlying the differences in yield formation among two parents (P1 and P2) and their F1 hybrid of cucumber, biomass production and whole source–sink dynamics were analyzed using a functional–structural plant model (FSPM) that simulates both the number and size of individual organs. Observations of plant development and organ biomass were recorded throughout the growth periods of the plants. The GreenLab Model was used to analyze the differences in fruit sett...
Source
#1Wenbo Zheng (CAS: Chinese Academy of Sciences)H-Index: 1
#2Lan Yan (CAS: Chinese Academy of Sciences)H-Index: 1
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 4 authors...
Source
#1Wenwen Zhang (CAS: Chinese Academy of Sciences)H-Index: 2
#2Kunfeng Wang (CAS: Chinese Academy of Sciences)H-Index: 17
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 5 authors...
Abstract In recent years, with the development of computing power and deep learning algorithms, pedestrian detection has made great progress. Nevertheless, once a detection model trained on generic datasets (such as PASCAL VOC and MS COCO) is applied to a specific scene, its precision is limited by the distribution gap between the generic data and the specific scene data. It is difficult to train the model for a specific scene, due to the lack of labeled data from that scene. Even though we mana...
2 CitationsSource
#1Kunfeng Wang (CAS: Chinese Academy of Sciences)H-Index: 17
#2Fei-Yue WangH-Index: 53
Last. Fuxin Li (OSU: Oregon State University)
view all 6 authors...
Source
#1Wenbo Zheng (CAS: Chinese Academy of Sciences)H-Index: 2
#2Kunfeng Wang (CAS: Chinese Academy of Sciences)H-Index: 17
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 3 authors...
Abstract To address the challenges of change detection in the wild, we present a novel background subtraction algorithm based on parallel vision and Bayesian generative adversarial networks (GANs). First, we use the median filtering algorithm for background image extraction. Then, we build the background subtraction model by using Bayesian GANs to classify all pixels into foreground and background, and use parallel vision theory to improve the background subtraction results in complex scenes. Th...
9 CitationsSource
Jun 14, 2020 in CVPR (Computer Vision and Pattern Recognition)
#2Lan Yan (CAS: Chinese Academy of Sciences)H-Index: 1
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 4 authors...
Visual reasoning between visual image and natural language description is a long-standing challenge in computer vision. While recent approaches offer a great promise by compositionality or relational computing, most of them are oppressed by the challenge of training with datasets containing only a limited number of images with ground-truth texts. Besides, it is extremely time-consuming and difficult to build a larger dataset by annotating millions of images with text descriptions that may very l...
Welcome to the new issue of the IEEE Transactions on Computational Social Systems (TCSS). I am grateful to report that, as of April 9, 2020,the Citescore of TCSS has reached to 5.26, a new high. Many thanks to all of you for your great effort and support.
Source
#1Yonglin Tian (CAS: Chinese Academy of Sciences)H-Index: 3
#2Kunfeng Wang (Huada: Beijing University of Chemical Technology)H-Index: 17
Last. Fei-Yue Wang (CAS: Chinese Academy of Sciences)H-Index: 53
view all 6 authors...
Abstract This paper focuses on the construction of strong local features and the effective fusion of image and LiDAR data for 3D object detection. We adopt different modalities of LiDAR data to generate rich features and present an adaptive and azimuth-aware network to aggregate local features from image, bird’s eye view maps and point cloud. Our network mainly consists of three subnetworks: ground plane estimation network, region proposal network and adaptive fusion network. The ground plane es...
Source
12345678910