7 Papers
16 Citations
Wei Ju is an academic researcher from Hefei University of Technology. The author has contributed to research in topics: Partial least squares regression & Object detection. The author has an hindex of 2, co-authored 7 publications. Previous affiliations of Wei Ju include Anhui University.
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Papers
Molecular spectroscopic wavelength selection using combined interval partial least squares and correlation coefficient optimization
Weiwei Jiang,Changhua Lu,Changhua Lu,Yu-jun Zhang,Wei Ju,Jizhou Wang,Jizhou Wang,Mingxia Xiao +7 more
TL;DR: In this paper, the authors combined Savitzky-Golay (SG) preprocessing, the correlation coefficient (CC) method, and synergy interval partial least squares (siPLS) algorithms to quantitatively analyze corn components using near-infrared spectroscopy data.
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RDNet: Regression Dense and Attention for Object Detection in Traffic Symbols
TL;DR: The use of a dense network structure has realized the diversity of different receptive fields in the process of multi-scale feature extraction and the ability to improve has been improved.
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Rapid Identification of Atmospheric Gaseous Pollutants Using Fourier-Transform Infrared Spectroscopy Combined with Independent Component Analysis
TL;DR: In this paper, independent component analysis (ICA) is applied to the spectral separation of heavily overlapped spectra of gaseous pollutants, which can shorten the identification time, as well as increase the identification rate.
PGNet: Pipeline Guidance for Human Key-Point Detection.
TL;DR: A novel network structure PGNet is proposed, which contains three parts: pipeline guidance strategy (PGS); Cross-Distance-IoU Loss (CIoU); and Cascaded Fusion Feature Model (CFFM), which contains rich semantic information but a lack of spatial information that results in information imbalance and feature extraction imbalance.
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Imbalanced heartbeat classification using EasyEnsemble technique and global heartbeat information
TL;DR: Wang et al. as discussed by the authors proposed a new method for classifying imbalanced heartbeat using EasyEnsemble technique with global heartbeat information, which can not only achieve the best overall performance, but also can significantly improve the performance of minority categories while maintaining the good performance of majority categories.
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