Deep Drug–Target Binding Affinity Prediction Base on Multiple Feature Extraction and Fusion by Zepeng Li, Yuni Zeng, Mingfeng Jiang, Bo Wei

Get full text

Integrated CNN‐LSTM for Photovoltaic Power Prediction based on Spatio‐Temporal Feature Fusion by Junwei Ma, Meiru Huo, Jinfeng Han, Yunfeng Liu, Shunfa Lu, Xiaokun Yu

“…This paper proposes a convolutional neural network‐long short‐term memory (CNN‐LSTM) network integration model based on spatio‐temporal feature fusion. Firstly, the temporal correlation of the PV features of the target power plant and the spatial correlation between the PV power of the target power plant and the PV power of the neighboring power plants are computed. …”
Get full text

(Pyridin-2-ylmethyl)porphyrins: synthesis, characterization and C–N oxidative fusion attempts by Berthelot, Mathieu, Echaubard, Julie, Bousfiha, Asmae, Devillers, Charles H.

Subjects: Get full text

Multi-feature fusion-based consumer perceived risk prediction and its interpretability study. by Lin Qi, Yunjie Xie, Qianqian Zhang, Jian Zhang, Yanhong Ma

Get full text

Industrial Printing Image Defect Detection Using Multi-Edge Feature Fusion Algorithm by Bangchao Liu, Youping Chen, Jingming Xie, Bing Chen

“…In this paper, we propose a new multi-edge feature fusion algorithm which is effective in solving this problem. …”
Get full text

Correction: Application of RhBMP-2 in Percutaneous Endoscopic Posterior Lumbar Interbody Fusion by Yunsheng Chen, Canhua Xu, Yaohong Wu, Jiangyou Shi, Rongchun Chen

Get full text

Automated and highly parallelized Bayesian optimization scheme for direct drive fusion experiments on OMEGA by V. Gopalaswamy, A. Lees, R. Ejaz, C. A. Thomas, T. J. B. Collins, K. S. Anderson, W. Ebmeyer, R. Betti

“…Finding the optimal implosion design on existing experimental facilities for inertial confinement fusion requires an exhaustive search of the vast design parameter space. …”
Get full text

Tumor Resection, Reconstruction, and Ankle Fusion for Recurrent Giant Cell Tumor of the Distal Tibia by Alok C. Agrawal, Mukund Madhav Ojha, Somok Banerjee

“…The patient underwent wide margin excision of tumor and ankle fusion using the contralateral fibula as a second pillar to increase the stability of construct. …”
Get full text

An indoor positioning method based on bluetooth array/PDR fusion using the SVD-EKF by Chenhui Li, Jie Zhen, Jianxin Wu

“…Aiming at the problem that the system positioning error increase in the complex and variable indoor environment, a fusion positioning method of Bluetooth array/PDR (Pedestrian Dead Reckoning) based on the SVD-EKF (Singular Value Decomposition–Extended Kalman Filter) is proposed. …”
Get full text

Research on Orbital Angular Momentum Mode Detection in an Atmospheric Environment with Fusion Transfer Learning by Chenghu Ke, Youmei Chen, Xizheng Ke

Get full text

Retracted: Generative Adversarial Networks for Unmanned Aerial Vehicle Object Detection with Fusion Technology by Journal of Advanced Transportation

Get full text

Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…Specifically, first, a redundancy-weighted feature fusion module is proposed, enabling the model to fully leverage valuable feature information, thereby improving its performance. …”
Get full text

Intelligent Target Detection in Synthetic Aperture Radar Images Based on Multi-Level Fusion by Qiaoyu Liu, Ziqi Ye, Chenxiang Zhu, Dongxu Ouyang, Dandan Gu, Haipeng Wang

Subjects: Get full text

Sensor fusion with high‐order moments constraints using projection‐based neural network by Yousef Alipouri, Reza Rafati Bonab, Lexuan Zhong

Subjects: Get full text

A Fusion Parameter Method for Classifying Freshness of Fish Based on Electrochemical Impedance Spectroscopy by Jian Sun, Yuhao Liu, Gangshan Wu, Yecheng Zhang, Rongbiao Zhang, X. J. Li

“…In order to eliminate the disadvantages of the multiparameter model, a data fusion method based on model similarity (DFMS) was proposed in this study. …”
Get full text

Attention-enhanced multimodal feature fusion network for clothes-changing person re-identification by Yongkang Ding, Jiechen Li, Hao Wang, Ziang Liu, Anqi Wang

“…Additionally, we introduce a multi-scale fusion attention mechanism that further enhances the model’s ability to capture both detailed and global structures, thereby improving recognition accuracy and robustness. …”
Get full text

Global TEC Map Fusion Through a Hybrid Deep Learning Model: RFGAN by Zhou Chen, Kecheng Zhou, Haimeng Li, Jing‐song Wang, Zhihai Ouyang, Xiaohua Deng

“…Our proposed deep learning hybrid model can be easily extended and widely applied to other fields of space science, especially in addressing observational data loss and multi‐source data fusion.…”
Get full text

Two-plasmon-decay instability stimulated by dual laser beams in inertial confinement fusion by C.-W. Lian, Y. Ji, R. Yan, J. Li, L.-F. Wang, Y.-K. Ding, J. Zheng

“…Two-plasmon-decay instability (TPD) poses a critical target preheating risk in direct-drive inertial confinement fusion. In this paper, TPD collectively driven by dual laser beams consisting of a normal-incidence laser beam (Beam-N) and a large-angle-incidence laser beam (Beam-L) is investigated via particle-in-cell simulations. …”
Get full text

Fusion of satellite-ground and inter-satellite AKA protocols for double-layer satellite networks by Jin CAO, Xiaoping SHI, Ruhui MA, Hui LI

Get full text

Temporal link prediction method based on community multi-features fusion and embedded representation by Yuhang ZHU, Lixin JI, Yingle LI, Haitao LI, Shuxin LIU

“…Dynamic networks integrates time attributes on the basis of static networks, and it contains multiple connotations such as the complexity and dynamics of the network structure.It is a better thinking object for studying complex network link prediction problems in the real world.Its high application value has attracted much attention in recent years.However, most of the research objects of traditional methods are still limited to static networks, and there are problems such as insufficient utilization of network time-domain evolution information and high time complexity.Combining sociological theory, a novel temporal link prediction method was proposed based on community multi-feature fusion embedding representation.The core idea of this method was to analyze the dynamic evolution characteristics of the network, learn the embedded representation vector of nodes within the community, and effectively fuse multiple features to measure the generation probability of the connection between nodes.The network was divided into several subgraphs by using community detection with collective influence weights and the Similarity index was proposed based on the collective influence.Then, the biased random walk and the Skip-gram were used to get the embedded vectors for every node and the Similarity index was proposed based on the random walk within the community.Integrating the collective influence, multiple central features of the community, and the representation vector learned within the community, the Similarity index was proposed based on the multi-features fusion.Compared with classical temporal link prediction methods, including moving average methods, embedded representation methods, and graph neural network methods, experimental results on six real data sets show that the proposed methods based on the random walk within the community and the multi-features fusion both achieve better prediction performance under the evaluation criteria of AUC.…”
Get full text