Search Results for author: Witold Pedrycz

Found 43 papers, 4 papers with code

BEND: Bagging Deep Learning Training Based on Efficient Neural Network Diffusion

no code implementations23 Mar 2024 Jia Wei, Xingjun Zhang, Witold Pedrycz

The originality of BEND comes from the first use of a neural network diffusion model to efficiently build base classifiers for bagging.

Efficient Neural Network

TrustGuard: GNN-based Robust and Explainable Trust Evaluation with Dynamicity Support

1 code implementation23 Jun 2023 Jie Wang, Zheng Yan, Jiahe Lan, Elisa Bertino, Witold Pedrycz

Among them, the spatial aggregation layer adopts a defense mechanism to robustly aggregate local trust, and the temporal aggregation layer applies an attention mechanism for effective learning of temporal patterns.

Decision Making

A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks

no code implementations11 Jun 2023 Saidul Islam, Hanae Elmekki, Ahmed Elsebai, Jamal Bentahar, Najat Drawel, Gaith Rjoub, Witold Pedrycz

Transformer is a deep neural network that employs a self-attention mechanism to comprehend the contextual relationships within sequential data.

Ensemble Reinforcement Learning: A Survey

no code implementations5 Mar 2023 Yanjie Song, P. N. Suganthan, Witold Pedrycz, Junwei Ou, Yongming He, Yingwu Chen, Yutong Wu

By offering guidance for future scientific research and engineering applications, this survey significantly contributes to the advancement of ERL.

Ensemble Learning Model Selection +2

Accelerated Fuzzy C-Means Clustering Based on New Affinity Filtering and Membership Scaling

no code implementations14 Feb 2023 Dong Li, Shuisheng Zhou, Witold Pedrycz

However, FCM and its many accelerated variants have low efficiency in the mid-to-late stage of the clustering process.


Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning

no code implementations25 Jun 2022 Jianglin Lu, Jie zhou, Yudong Chen, Witold Pedrycz, Kwok-Wai Hung

Specifically, ATH characterizes the domain distribution gap by the discrepancy between two asymmetric hash functions, and minimizes the feature gap with the help of a novel adaptive bipartite graph constructed on cross-domain data.

Graph Learning Retrieval +1

Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning

no code implementations30 Apr 2022 Cuiying Huo, Dongxiao He, Yawen Li, Di Jin, Jianwu Dang, Weixiong Zhang, Witold Pedrycz, Lingfei Wu

However, the existing contrastive learning methods are inadequate for heterogeneous graphs because they construct contrastive views only based on data perturbation or pre-defined structural properties (e. g., meta-path) in graph data while ignore the noises that may exist in both node attributes and graph topologies.

Attribute Contrastive Learning

Logistics in the Sky: A Two-phase Optimization Approach for the Drone Package Pickup and Delivery System

no code implementations4 Apr 2022 Fangyu Hong, Guohua Wu, Qizhang Luo, Huan Liu, Xiaoping Fang, Witold Pedrycz

Different from the previous urban distribution mode that depends on trucks, this paper proposes a novel package pick-up and delivery mode and system in which multiple drones collaborate with automatic devices.


Vision Transformer with Convolutions Architecture Search

no code implementations20 Mar 2022 Haichao Zhang, Kuangrong Hao, Witold Pedrycz, Lei Gao, Xuesong Tang, Bing Wei

The high-performance backbone network searched by VTCAS introduces the desirable features of convolutional neural networks into the Transformer architecture while maintaining the benefits of the multi-head attention mechanism.

Image Classification object-detection +2

Robust and Precise Facial Landmark Detection by Self-Calibrated Pose Attention Network

no code implementations23 Dec 2021 Jun Wan, Hui Xi, Jie zhou, Zhihui Lai, Witold Pedrycz, Xu Wang, Hang Sun

We show that by integrating the BALI fields and SCPA model into a novel self-calibrated pose attention network, more facial prior knowledge can be learned and the detection accuracy and robustness of our method for faces with large poses and heavy occlusions have been improved.

Facial Landmark Detection

An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem

no code implementations15 Jul 2021 Bingjie Li, Guohua Wu, Yongming He, Mingfeng Fan, Witold Pedrycz

Vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem, and many models and algorithms have been proposed to solve the VRP and its variants.

Combinatorial Optimization

A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems

no code implementations10 Mar 2021 Yongming He, Guohua Wu, Yingwu Chen, Witold Pedrycz

This offers a novel and general paradigm that combines RL with OR approaches to solving scheduling problems, which leverages the respective strengths of RL and OR: The MDP narrows down the search space of the original problem through an RL method, while the mixed-integer programming process is settled by an OR algorithm.

Combinatorial Optimization Earth Observation +3

LDNet: End-to-End Lane Marking Detection Approach Using a Dynamic Vision Sensor

1 code implementation17 Sep 2020 Farzeen Munir, Shoaib Azam, Moongu Jeon, Byung-Geun Lee, Witold Pedrycz

Traditional lane detection methods incorporate handcrafted or deep learning-based features followed by postprocessing techniques for lane extraction using frame-based RGB cameras.

Autonomous Driving Decoder +1

Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusion

1 code implementation31 Aug 2020 Young-min Song, Young-chul Yoon, Kwangjin Yoon, Moongu Jeon, Seong-Whan Lee, Witold Pedrycz

One affinity, for position and motion, is computed by using the GMPHD filter, and the other affinity, for appearance is computed by using the responses from a single object tracker such as a kernalized correlation filter.

Instance Segmentation Multi-Object Tracking +2

Bottom-up mechanism and improved contract net protocol for the dynamic task planning of heterogeneous Earth observation resources

no code implementations13 Jul 2020 Baoju Liu, Min Deng, Guohua Wu, Xinyu Pei, Haifeng Li, Witold Pedrycz

It also demonstrates that this method can help to efficiently obtain replanning schemes based on original scheme in dynamic environments.

Earth Observation

Integrating Variable Reduction Strategy with Evolutionary Algorithm for Solving Nonlinear Equations Systems

no code implementations13 Jul 2020 Aijuan Song, Guohua Wu, Witold Pedrycz

To test the effectiveness of VRS in dealing with NESs, this paper integrates VRS into two existing state-of-the-art EA methods (i. e., MONES and DRJADE), respectively.

Exponentially Weighted l_2 Regularization Strategy in Constructing Reinforced Second-order Fuzzy Rule-based Model

no code implementations2 Jul 2020 Congcong Zhang, Sung-Kwun Oh, Witold Pedrycz, Zunwei Fu, Shanzhen Lu

In the conventional Takagi-Sugeno-Kang (TSK)-type fuzzy models, constant or linear functions are usually utilized as the consequent parts of the fuzzy rules, but they cannot effectively describe the behavior within local regions defined by the antecedent parts.

L2 Regularization

Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving

no code implementations1 Jun 2020 Farzeen Munir, Shoaib Azam, Muhammd Aasim Rafique, Ahmad Muqeem Sheri, Moongu Jeon, Witold Pedrycz

A thermal camera captures an image using the heat difference emitted by objects in the infrared spectrum, and object detection in thermal images becomes effective for autonomous driving in challenging conditions.

Autonomous Driving Domain Adaptation +6

A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes

no code implementations12 May 2020 Kaijie Xu, Witold Pedrycz, Zhiwu Li, Yinghui Quan, Weike Nie

With the information granules we build a characteristic matrix of the gene data to capture the fluctuation trend of the expression value between consecutive conditions to mine the ideal bi-clusters.

Clustering Time Series +1

Residual-driven Fuzzy C-Means Clustering for Image Segmentation

no code implementations15 Apr 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou

Due to its inferior characteristics, an observed (noisy) image's direct use gives rise to poor segmentation results.

Clustering Image Segmentation +2

Augmentation of the Reconstruction Performance of Fuzzy C-Means with an Optimized Fuzzification Factor Vector

no code implementations13 Apr 2020 Kaijie Xu, Witold Pedrycz, Zhiwu Li

In this paper, to enhance the quality of the degranulation (reconstruction) process, we augment the FCM-based degranulation mechanism by introducing a vector of fuzzification factors (fuzzification factor vector) and setting up an adjustment mechanism to modify the prototypes and the partition matrix.

Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix

no code implementations3 Apr 2020 Kaijie Xu, Witold Pedrycz, Zhiwu Li, Mengdao Xing

By proposing the augmented scheme, we dwell on a novel collection of granulation-degranulation mechanisms.


Agile Earth observation satellite scheduling over 20 years: formulations, methods and future directions

no code implementations13 Mar 2020 Xinwei Wang, Guohua Wu, Lining Xing, Witold Pedrycz

Agile satellites with advanced attitude maneuvering capability are the new generation of Earth observation satellites (EOSs).

Earth Observation Scheduling

Kullback-Leibler Divergence-Based Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation

no code implementations21 Feb 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou

Considering these feature sets as data of clustering, an modified FCM algorithm is proposed, which introduces a KL divergence term in the partition matrix into its objective function.

Clustering Image Segmentation +2

Key Points Estimation and Point Instance Segmentation Approach for Lane Detection

10 code implementations16 Feb 2020 Yeongmin Ko, Younkwan Lee, Shoaib Azam, Farzeen Munir, Moongu Jeon, Witold Pedrycz

In the case of traffic line detection, an essential perception module, many condition should be considered, such as number of traffic lines and computing power of the target system.

Autonomous Driving Clustering +4

Residual-Sparse Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet frames

no code implementations14 Feb 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou, Jun Zhao

To further enhance the segmentation effects of the improved FCM algorithm, we also employ the morphological reconstruction to smoothen the labels generated by clustering.

Clustering Image Segmentation +1

An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Non-stationary Data Streams

no code implementations26 Aug 2018 Mahardhika Pratama, Witold Pedrycz, Geoffrey I. Webb

DEVFNN is developed under the stacked generalization principle via the feature augmentation concept where a recently developed algorithm, namely gClass, drives the hidden layer.

Continual Learning feature selection

Online Tool Condition Monitoring Based on Parsimonious Ensemble+

no code implementations6 Nov 2017 Mahardhika Pratama, Eric Dimla, Edwin Lughofer, Witold Pedrycz, Tegoeh Tjahjowidowo

The paper presents advancement of a newly developed ensemble learning algorithm, pENsemble+, where online active learning scenario is incorporated to reduce operator labelling effort.

Active Learning Ensemble Learning +1

Evolving Ensemble Fuzzy Classifier

no code implementations18 May 2017 Mahardhika Pratama, Witold Pedrycz, Edwin Lughofer

pENsemble adopts a dynamic ensemble structure to output a final classification decision where it features a novel drift detection scenario to grow the ensemble structure.

Ensemble Learning Ensemble Pruning +1

Aggregation of Classifiers: A Justifiable Information Granularity Approach

no code implementations15 Mar 2017 Tien Thanh Nguyen, Xuan Cuong Pham, Alan Wee-Chung Liew, Witold Pedrycz

In this study, we introduce a new approach to combine multi-classifiers in an ensemble system.

Global and Local Structure Preserving Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature Selection

no code implementations2 Jun 2015 Nan Zhou, Yangyang Xu, Hong Cheng, Jun Fang, Witold Pedrycz

In this paper, we propose a global and local structure preserving sparse subspace learning (GLoSS) model for unsupervised feature selection.

feature selection

Entropic one-class classifiers

no code implementations28 Jul 2014 Lorenzo Livi, Alireza Sadeghian, Witold Pedrycz

The one-class classification problem is a well-known research endeavor in pattern recognition.

Benchmarking General Classification +2

An adaptive Simulated Annealing-based satellite observation scheduling method combined with a dynamic task clustering strategy

no code implementations14 Jan 2014 Guohua Wu, Huilin Wang, Haifeng Li, Witold Pedrycz, Dishan Qiu, Manhao Ma, Jin Liu

In this study, we present an adaptive Simulated Annealing based scheduling algorithm aggregated with a dynamic task clustering strategy (or ASA-DTC for short) for satellite observation scheduling problems (SOSPs).

Clustering Scheduling

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