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Smart Agriculture System based on Internet of Things using Kernel K-Means with Support Vector Machine Conference paper
Zhong, Junhong, Lai, Qi. Smart Agriculture System based on Internet of Things using Kernel K-Means with Support Vector Machine[C]:Institute of Electrical and Electronics Engineers Inc., 2024.
Authors:  Zhong, Junhong;  Lai, Qi
Favorite | TC[Scopus]:0 | Submit date：2024/09/03
Data Cleaning  Internet Of Things  Kernel K-means  Smart Agriculture  Support Vector Machine  
Real-Time Surface Identification System for Variable Walking Speeds of Biped Robots Journal article
Luo, Aiwen, Bhattacharya, Sandip, Miura-Mattausch, Mitiko, Zhou, Yicong, Mattausch, Hans J.. Real-Time Surface Identification System for Variable Walking Speeds of Biped Robots[J]. IEEE Embedded Systems Letters, 2024, 16(2), 130-133.
Authors:  Luo, Aiwen;  Bhattacharya, Sandip;  Miura-Mattausch, Mitiko;  Zhou, Yicong;  Mattausch, Hans J.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.7/1.6 | Submit date：2024/02/23
Biped Robot  Force Sensor  Real-time Support Vector Machine (Svm)  Surface Identification  Variable Walking Speed  
A multifeature fusion model for surface roughness measurement of cold-rolled strip steel based on laser speckle Journal article
Li, Siyi, Peng, Gongzhuang, Xu, Dong, Shao, Meiqi, Wang, Xiaochen, Yang, Quan. A multifeature fusion model for surface roughness measurement of cold-rolled strip steel based on laser speckle[J]. Measurement: Journal of the International Measurement Confederation, 2024, 227, 114319.
Authors:  Li, Siyi;  Peng, Gongzhuang;  Xu, Dong;  Shao, Meiqi;  Wang, Xiaochen; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:5.2/4.8 | Submit date：2024/04/02
Convolution Block Attention Mechanism Module  Laser Speckle  Multifeature Fusion  Support Vector Machine  Surface Roughness  
Identifying key features of resilient students in digital reading: Insights from a machine learning approach. Journal article
Jia-qi Zheng, Kwok-cheung Cheung, Pou-seong Sit. Identifying key features of resilient students in digital reading: Insights from a machine learning approach.[J]. Education and Information Technologies, 2024, 29(2), 2277-2301.
Authors:  Jia-qi Zheng;  Kwok-cheung Cheung;  Pou-seong Sit
Favorite | TC[WOS]:8 TC[Scopus]:9  IF:4.8/4.8 | Submit date：2023/07/04
Support Vector Machine  Digital Reading  Academic Resilience  Asia  Pisa  
The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders Journal article
Yan Han, Xinglin Zeng, Lin Hua, Xingping Quan, Ying Chen, Manfei Zhou, Yaochen Chuang, Yang Li, Shengpeng Wang, Xu Shen, Lai Wei, Zhen Yuan, Yonghua Zhao. The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders[J]. Microbiome, 2024, 12(1), 12.
Authors:  Yan Han;  Xinglin Zeng;  Lin Hua;  Xingping Quan;  Ying Chen; et al.
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:13.8/17.9 | Submit date：2024/04/03
Electroencephalography  Metabolomics  Metagenomics  Neurocognitive Disorders  Proteomics  Support Vector Machine  
Identifying Key Contextual Factors of Digital Reading Literacy Through a Machine Learning Approach Journal article
Chen, Fu, Sakyi, Alfred, Cui, Ying. Identifying Key Contextual Factors of Digital Reading Literacy Through a Machine Learning Approach[J]. JOURNAL OF EDUCATIONAL COMPUTING RESEARCH, 2022, 60(7), 1763-1795.
Authors:  Chen, Fu;  Sakyi, Alfred;  Cui, Ying
Favorite | TC[WOS]:11 TC[Scopus]:14  IF:4.0/5.0 | Submit date：2022/05/17
Digital Reading  Reading Literacy  Large-scale Assessment  Machine Learning  Support Vector Machine  
Short-Term Travel-Time Prediction using Support Vector Machine and Nearest Neighbor Method Book chapter
出自: Transportation Research Record, 2455 TELLER RD, THOUSAND OAKS, CA 91320:SAGE PUBLICATIONS INC, 2022, 页码:353-365
Authors:  Meng, Meng;  Toan, Trinh Dinh;  Wong, Yiik Diew;  Lam, Soi Hoi
Favorite | TC[WOS]:13 TC[Scopus]:15 | Submit date：2023/01/30
Artificial Intelligence And Advanced Computing Applications  Data Analytics  Data And Data Science  Information Systems And Technology  Machine Learning (Artificial Intelligence)  Supervised Learning  Support Vector Machines  Traffic Predication  
Learning Performance of Weighted Distributed Learning With Support Vector Machines Journal article
Zou, Bin, Jiang, Hongwei, Xu, Chen, Xu, Jie, You, Xinge, Tang, Yuan Yan. Learning Performance of Weighted Distributed Learning With Support Vector Machines[J]. IEEE Transactions on Cybernetics, 2021, 53(7), 4630 - 4641.
Authors:  Zou, Bin;  Jiang, Hongwei;  Xu, Chen;  Xu, Jie;  You, Xinge; et al.
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:9.4/10.3 | Submit date：2022/05/13
Convergence Rate  Learning Performance  Support Vector Machine  Weighted Distributed  
Brain network excitatory/inhibitory imbalance is a biomarker for drug-naive Rolandic epilepsy: A radiomics strategy Journal article
Dai, Xi Jian, Liu, Heng, Yang, Yang, Wang, Yongjun, Wan, Feng. Brain network excitatory/inhibitory imbalance is a biomarker for drug-naive Rolandic epilepsy: A radiomics strategy[J]. EPILEPSIA, 2021, 62(10), 2426-2438.
Authors:  Dai, Xi Jian;  Liu, Heng;  Yang, Yang;  Wang, Yongjun;  Wan, Feng
Favorite | TC[WOS]:19 TC[Scopus]:17  IF:6.6/6.2 | Submit date：2021/12/08
Benign Epilepsy Of Childhood With Centro-temporal Spikes  Classification  Cognitive Network  Dynamic Causal Modeling  Excitation And Inhibition Imbalance  Machine Learning  Rolandic Epilepsy  Support Vector Machine  
Brain rhythm sequencing and its application for EEG-based emotion recognition Conference paper
Jia Wen Li, Shovan Barma, Sio Hang Pun, Mang I Vai, Feng Wan, Wai Sun Liu, Peng Un Mak. Brain rhythm sequencing and its application for EEG-based emotion recognition[C]:IEEE, 2021.
Authors:  Jia Wen Li;  Shovan Barma;  Sio Hang Pun;  Mang I Vai;  Feng Wan; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2021/12/08
Brain Rhythm Sequencing  Electroencephalography (Eeg)  Emotion Recognition  Optimal Feature  Support Vector Machine (Svm)