| 1 | Application of improved virtual sample and sparse representation in face recognition显示文摘Sparse representation plays an important role in the research of face recognition.As a deformable sample classification task,face recognition is often used to test the performance of classification algorithms.In face recognition,differences in expression,angle,posture,and lighting conditions have become key factors that affect recognition accuracy.Essentially,there may be significant differences between different image samples of the same face,which makes image classification very difficult.Therefore,how to build a robust virtual image representation becomes a vital issue.To solve the above problems,this paper proposes a novel image classification algorithm.First,to better retain the global features and contour information of the original sample,the algorithm uses an improved non‐linear image representation method to highlight the low‐intensity and high‐intensity pixels of the original training sample,thus generating a virtual sample.Second,by the principle of sparse representation,the linear expression coefficients of the original sample and the virtual sample can be calculated,respectively.After obtaining these two types of coefficients,calculate the distances between the original sample and the test sample and the distance between the virtual sample and the test sample.These two distances are converted into distance scores.Finally,a simple and effective weight fusion scheme is adopted to fuse the classification scores of the original image and the virtual image.The fused score will determine the final classification result.The experimental results show that the proposed method outperforms other typical sparse representation classification methods. | Yongjun Zhang Zewei Wang Xuexue Zhang Zhongwei Cui Bob Zhang Jinrong Cui Lamin LJanneh | 2023 | CAAI Transactions on Intelligence Technology2023，8，4： | 0 |
| 2 | Wearable Fiber‑Based Supercapacitors Enabled by Additive‑Free Aqueous MXene Inks for Self‑Powering Healthcare Sensors显示文摘Wearable fiber-based electronics have found diverse applications including energy storage,healthcare or thermal management,etc.In particular,additive-free aqueous inks play significant roles in fabrication of wearable fiber-based devices,owning to their nontoxic nature and ease of manufacturing.Herein,wearable carbon fiber-based asymmetric supercapacitors(WASSC)are developed based on additive-free aqueous MXene inks,for self-powering healthcare sensors.The sediments of MXene without further modification are used as inks.Furthermore,combined with additive-free aqueous MXene/polyaniline(MP)inks,WASSC,with a wide voltage window and high capacitance is developed for practical energy supply.Impressively,WASSC has been successfully utilized to power wearable pressure sensors that could monitor motions and pulse signals.This wearable self-powered monitoring system on can accurately monitor the human motions,pronunciation,swallow or wrist pulse,without using the rigid batteries.This advantage realizes a great potential in simple and cost effective monitoring of human health and activities.Besides,self-powered system enables waste recycling of MXene and provides an effective approach for designing wearable and fiber-based self-powered sensors. | Junlin Ma Zewei Cui Yuhang Du Jianxin Zhang Changkai Sun Chengyi Hou Nan Zhu | 2022 | Advanced Fiber Materials2022，4，6： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员