An integrated simplicial neural network with neuro-fuzzy network for graph embedding DOI
Phu Pham

International Journal of Machine Learning and Cybernetics, Journal Year: 2024, Volume and Issue: unknown

Published: May 22, 2024

Language: Английский

An Emerging Incremental Fuzzy Concept-Cognitive Learning Model Based on Granular Computing and Conceptual Knowledge Clustering DOI
X. Deng, Jinhai Li, Yuhua Qian

et al.

IEEE Transactions on Emerging Topics in Computational Intelligence, Journal Year: 2024, Volume and Issue: 8(3), P. 2417 - 2432

Published: Feb. 14, 2024

Fuzzy granular concepts are fundamental units in developing computational intelligence approaches based on fuzzy concept-cognitive learning. However, existing models this field merely focus the information provided by induced objects, ignoring that of those attributes. Consequently, these underutilize and weaken classification ability. To solve problem, we propose an effective learning model, which incorporates attribute basis object concepts. be concrete, firstly introduce notion a concept construct space. Secondly, obtain clustering space optimizing threshold is used to fuse similar concepts, then form lower upper approximation spaces through set approximation. In addition, explain mechanism new incremental model for label prediction integrating spaces. Finally, show performance proposed 28 datasets comparing it with 10 classical machine algorithms 17 similarity-based algorithms, evaluate ability our model. The experimental results demonstrate feasibility effectiveness method.

Language: Английский

Citations

8
Learning adaptive shift and task decoupling for discriminative one-step person search DOI
Qixian Zhang, Duoqian Miao, Qi Zhang

et al.

Knowledge-Based Systems, Journal Year: 2024, Volume and Issue: unknown, P. 112483 - 112483

Published: Sept. 1, 2024

Language: Английский

Citations

7
NFMPAtt-Unet: Neighborhood Fuzzy C-means Multi-scale Pyramid Hybrid Attention Unet for medical image segmentation DOI
Xinpeng Zhao,

Weihua Xu

Neural Networks, Journal Year: 2024, Volume and Issue: 178, P. 106489 - 106489

Published: June 22, 2024

Language: Английский

Citations

6
A novel information fusion method using improved entropy measure in multi-source incomplete interval-valued datasets DOI
Weihua Xu, Ke Cai, Debby D. Wang

et al.

International Journal of Approximate Reasoning, Journal Year: 2023, Volume and Issue: 164, P. 109081 - 109081

Published: Nov. 10, 2023

Language: Английский

Citations

12
Optimal scale selection approach for classification based on generalized multi-scale formal context DOI
Fei Wang, Jinhai Li, Chongchong Yu

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 152, P. 111277 - 111277

Published: Jan. 15, 2024

Language: Английский

Citations

4
Matrix-based approximation dynamic update approach to multi-granulation neighborhood rough sets for intuitionistic fuzzy ordered datasets DOI
Xiaoyan Zhang, Jinghong Wang,

Jianglong Hou

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 163, P. 111915 - 111915

Published: Sept. 1, 2024

Language: Английский

Citations

4
Feature selection and information fusion based on preference ranking organization method in interval-valued multi-source decision-making information systems DOI
Weihua Xu,

Zhenyuan Tian

Information Sciences, Journal Year: 2025, Volume and Issue: 700, P. 121860 - 121860

Published: Jan. 7, 2025

Language: Английский

Citations

0
The relationship among some special concepts from the perspective of formal context restoration DOI
Siyu Zhao, Jianjun Qi, Ling Wei

et al.

Applied Intelligence, Journal Year: 2025, Volume and Issue: 55(4)

Published: Jan. 13, 2025

Language: Английский

Citations

0
Parameter efficient face frontalization in image sequences via GAN inversion DOI Creative Commons
Mohamad Hasan Ahmadi,

Nima Kambarani,

M.R. Mohammadi

et al.

IET Image Processing, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 1, 2025

Abstract Processing facial images with varying poses is a significant challenge. Most existing face frontalization methods rely on heavy architectures that struggle small datasets and produce low‐quality images. Additionally, although video frames provide richer information, these typically use single due to the lack of suitable multi‐image datasets. To address issues, parameter‐efficient framework for high‐quality in both multi‐frame scenarios proposed. First, high‐quality, diverse dataset created tasks. Second, novel single‐image method introduced by combining GAN inversion transfer learning. This approach reduces number trainable parameters over 91% compared while achieving far more photorealistic results than GAN‐based methods. Finally, this extended sequences images, using attention mechanisms merge information from multiple frames. artefacts like eye blinks improves reconstruction quality. Experiments demonstrate outperforms pSp, state‐of‐the‐art method, 0.15 LPIPS improvement 0.10 increase ID similarity. further identity preservation 0.87, showcasing its effectiveness frontal‐view reconstructions.

Language: Английский

Citations

0
Concept cognition over knowledge graphs: A perspective from mining multi-granularity attribute characteristics of concepts DOI
Xin Hu,

Deju Huang,

Jiangli Duan

et al.

Information Processing & Management, Journal Year: 2025, Volume and Issue: 62(4), P. 104095 - 104095

Published: Feb. 11, 2025

Language: Английский

Citations

0