no code implementations • 20 Nov 2023 • Chong Li, Zhun Fan, Ying Chen, Huibiao Lin, Laura Moretti, Giuseppe Loprencipe, Weihua Sheng, Kelvin C. P. Wang
Meanwhile, these models can not automatically correct errors in the prediction, nor can it adapt to the changes of the environment to automatically extract and detect thin cracks.
1 code implementation • 15 Jun 2023 • Jiafan Zhuang, Duan Yuan, Rihong Yan, Weixin Huang, Wenji Li, Zhun Fan
In this work, we build and present a UAVDE dataset for UAV distance estimation, in which distance between two UAVs is obtained by UWB sensors.
no code implementations • 28 Jul 2022 • Guijie Zhu, Zhun Fan, Jiacheng Liu, Duan Yuan, Peili Ma, Meihua Wang, Weihua Sheng, Kelvin C. P. Wang
In this paper, an efficient and effective end-to-end network for automatic pavement crack segmentation, called RHA-Net, is proposed to improve the pavement crack segmentation accuracy.
no code implementations • 25 Jun 2022 • Chen Wang, Minqiang Gu, Wenxi Kuang, Dongliang Wang, Weicheng Luo, Zhaohui Shi, Zhun Fan
This study proposes a distributed algorithm that makes agents' adaptive grouping entrap multiple targets via automatic decision making, smooth flocking, and well-distributed entrapping.
no code implementations • 29 Jul 2021 • Tianxiao Gao, Wu Wei, Zhongbin Cai, Zhun Fan, Shane Xie, Xinmei Wang, Qiuda Yu
In this paper, we propose a network injected with contextual information (CI-Net) to solve the problem.
Ranked #33 on Semantic Segmentation on SUN-RGBD (using extra training data)
no code implementations • 29 Oct 2020 • Jiahong Wei, Zhun Fan
Recently, many methods based on hand-designed convolutional neural networks (CNNs) have achieved promising results in automatic retinal vessel segmentation.
no code implementations • 1 Jul 2020 • Zhun Fan, Chong Li, Ying Chen, Jiahong Wei, Giuseppe Loprencipe, Xiaopeng Chen, Paola Di Mascio
Finally, the hierarchical feature learning module is designed to obtain a multi-scale features from the high to low-level convolutional layers, which are integrated to predict pixel-wise crack detection.
no code implementations • 8 Feb 2020 • Zhun Fan, Chong Li, Ying Chen, Paola Di Mascio, Xiaopeng Chen, Guijie Zhu, Giuseppe Loprencipe
In this paper, we propose an ensemble of convolutional neural networks (without a pooling layer) based on probability fusion for automated pavement crack detection and measurement.
no code implementations • 18 Jan 2020 • Zhun Fan, Jiahong Wei, Guijie Zhu, Jiajie Mo, Wenji Li
The accurate retinal vessel segmentation (RVS) is of great significance to assist doctors in the diagnosis of ophthalmology diseases and other systemic diseases.
no code implementations • 31 Oct 2019 • Zhun Fan, Zhaojun Wang, Xiaomin Zhu, Bingliang Hu, Anmin Zou, Dongwei Bao
Most existing swarm pattern formation methods depend on a predefined gene regulatory network (GRN) structure that requires designers' priori knowledge, which is difficult to adapt to complex and changeable environments.
2 code implementations • 28 Jun 2019 • Zhun Fan, Jiajie Mo, Benzhang Qiu, Wenji Li, Guijie Zhu, Chong Li, Jianye Hu, Yibiao Rong, Xinjian Chen
Compared with other convolution networks utilizing standard convolution for feature extraction, the proposed method utilizes octave convolutions and octave transposed convolutions for learning multiple-spatial-frequency features, thus can better capture retinal vasculatures with varying sizes and shapes.
1 code implementation • 3 Jun 2019 • Zhun Fan, Jiewei Lu, Benzhang Qiu, Tao Jiang, Kang An, Alex Noel Josephraj, Chuliang Wei
The proposed CNN-DC can achieve 99. 26% accuracy for steel bar counting and 4. 1% center offset for center localization on the established steel bar dataset, which demonstrates that the proposed CNN-DC can perform well on automated steel bar counting and center localization.
no code implementations • 2 Jun 2019 • Zhun Fan, Zhaojun Wang, Wenji Li, Yutong Yuan, Yugen You, Zhi Yang, Fuzan Sun, Jie Ruan, Zhaocheng Li
In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the convergence and diversity of working populations.
no code implementations • 16 Dec 2018 • Zhun Fan, Wenji Li, Zhaojun Wang, Yutong Yuan, Fuzan Sun, Zhi Yang, Jie Ruan, Zhaocheng Li, Erik Goodman
In the top sub-population, the search process is divided into two different stages --- push and pull stages. An adaptive DE variant with three trial vector generation strategies is employed in the proposed PPS-DE.
1 code implementation • 9 Sep 2018 • Jiewei Lu, Zhun Fan, Ce Zheng, Jingan Feng, Longtao Huang, Wenji Li, Erik D. Goodman
Telemedicine, which has great potential to alleviate the growing demand of the diagnosis of ophthalmologic diseases, is an effective method to achieve timely strabismus detection.
no code implementations • 10 Feb 2018 • Zhun Fan, Yi Fang, Wenji Li, Xinye Cai, Caimin Wei, Erik Goodman
The experimental results manifest that MOEA/D-ACDP is significantly better than the other four CMOEAs on these test instances and the real-world case, which indicates that ACDP is more effective for solving CMOPs.
no code implementations • 4 Feb 2018 • Zhun Fan, Zhongxing Li, Benzhang Qiu, Wenji Li, Jianye Hu, Alex Noel Josephraj, Heping Chen
In this paper, we present a global texture-shape 3D feature descriptor which can be utilized in a system of object recognition and grasping, and can perform object sorting tasks well.
1 code implementation • 1 Feb 2018 • Zhun Fan, Yuming Wu, Jiewei Lu, Wenji Li
In this paper, a supervised method based on deep learning is proposed, which has the capability of dealing with different pavement conditions.
no code implementations • 15 Sep 2017 • Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman
Compared with other CMOEAs, the proposed PPS method can more efficiently get across infeasible regions and converge to the feasible and non-dominated regions by applying push and pull search strategies at different stages.
no code implementations • 27 Jul 2017 • Zhun Fan, Wenji Li, Xinye Cai, Han Huang, Yi Fang, Yugen You, Jiajie Mo, Caimin Wei, Erik Goodman
In order to evaluate the performance of MOEA/D-IEpsilon, a new set of CMOPs with two and three objectives is designed, having large infeasible regions (relative to the feasible regions), and they are called LIR-CMOPs.
no code implementations • 4 Jan 2017 • Zhun Fan, Jiewei Lu, Wenji Li, Caimin Wei, Han Huang, Xinye Cai, Xinjian Chen
In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images.
no code implementations • 21 Dec 2016 • Zhun Fan, Wenji Li, Xinye Cai, Hui Li, Caimin Wei, Qingfu Zhang, Kalyanmoy Deb, Erik D. Goodman
Multi-objective evolutionary algorithms (MOEAs) have progressed significantly in recent decades, but most of them are designed to solve unconstrained multi-objective optimization problems.
no code implementations • 1 Apr 2015 • Zhun Fan, Wenji Li, Xinye Cai, Huibiao Lin, Shuxiang Xie, Erik Goodman
In this paper, we design a set of multi-objective constrained optimization problems (MCOPs) and propose a new repair operator to address them.