Nonlinear compensation-based self-positioning method for rail transit train by HAN Zhixing

“…Afterwards, the distance of the train to the next station was calculated based on the fixed train operation diagram, thus to realize positioning. …”
Get full text

Feather teaching and training based on Kinect sensor and gesture recognition technology by Luoluo Zhang, Pin Zhong

“…The badminton teaching auxiliary training system is designed from bone information collection and fusion, bone point coordinate angle feature extraction, and badminton action classification and recognition. …”
Get full text

Lightweight Detection of Train Underframe Bolts Based on SFCA-YOLOv8s by Zixiao Li, Jinjin Li, Chuanlong Zhang, Huajun Dong

“…To achieve efficient detection, a lightweight detection method based on SFCA-YOLOv8s is proposed. The underframe bolt images are captured by a self-designed track-based inspection robot, and a dataset is constructed by mixing simulated platform images with real train underframe bolt images. …”
Get full text

Underground Personnel Positioning Method Based on Self-training and NLOS Suppression by SHAO Xiaoqiang, HAN Zehui, MA Bo, YANG Yongde, YUAN Zewen, LI Xin

“…[Methods] In order to solve the problem that the existing supervised learning methods for NLOS identification and suppression require long time, labor intensive feature, and high cost became of the needs to obtain training data and label allocation, a method for underground personnel positioning based on self-training and suppression of NLOS is proposed, and a new general data fusion framework is designed. …”
Get full text

A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing by Ahmeed Yinusa, Misa Faezipour

“…We then applied a multi-layered defense strategy, including adversarial training with FGSM and PGD examples and feature squeezing techniques such as bit-depth reduction and Gaussian blurring. …”
Get full text

Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

Get full text

Webshell malicious traffic detection method based on multi-feature fusion by Yuan LI, Yunpeng WANG, Tao LI, Baoqiang MA

“…Webshell is the most common malicious backdoor program for persistent control of Web application systems, which poses a huge threat to the safe operation of Web servers.For most Webshell detection method based on the request packet data for training, the method for web-based Webshell recognition effect is poorer, and the model of training efficiency is low.In response to the above problems, a Webshell malicious traffic detection method based on multi-feature fusion was proposed.The method was characterized by the three dimensions of Webshell packet meta information, packet payload content and traffic access behavior.Combining domain knowledge, feature extraction of request and response packets in the data stream.Transformed into feature extraction information for information fusion, forming a discriminant model that could detect different types of attacks.Compared with the previous research method, the accuracy rate of the method here in the two classification of normal and malicious traffic has been improved to 99.25%.The training efficiency and detection efficiency have also been significantly improved, and the training time and detection time have been reduced by 95.73% and 86.14%.…”
Get full text

An Indoor Scene Classification Method for Service Robot Based on CNN Feature by Shaopeng Liu, Guohui Tian

“…However, this method cannot obtain satisfying indoor scene classification results because of overfitting when scene training datasets are insufficient. To solve this problem, an indoor scene classification method is proposed in this paper, which utilizes CNN feature of scene images to generate scene category features to classify scenes by a novel feature matching algorithm. …”
Get full text

Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…Then, in MATLAB software, the time series of spectral bands were constructed and using them, temporal profiles of NDVI for any crop were extracted to identify the unique phenological features of crops. Then, the functions developed based on the phenological characteristics of crops were applied to the time series of the bands and a feature channel was obtained for each crop that in two separate processes, once bands and once again feature channels were used as input to the CNN and the network was trained and the results of network performance on crop classification in the test site, were compared.Results and discussion:In the first stage, the time series of bands formed the input of the deep convectional neural network and the network was trained in the training area, using the tempo-spectral information of bands as the input channels and crops ground samples as the related labels. …”
Get full text

Enhancing UAS-Based Multispectral Semantic Segmentation Through Feature Engineering by Elena Vollmer, Mishal Benz, James Kahn, Leon Klug, Rebekka Volk, Frank Schultmann, Markus Gotz

“…A comprehensive ablation study is performed on a novel, uncrewed aircraft system-based dataset from two German cities to detect thermal urban features. …”
Get full text

Distributed Typhoon Track Prediction Based on Complex Features and Multitask Learning by Yongjiao Sun, Yaning Song, Baiyou Qiao, Boyang Li

“…To this end, we presented a novel typhoon track prediction framework comprising complex historical features—climatic, geographical, and physical features—as well as a deep-learning network based on multitask learning. …”
Get full text

Research on Image Feature Extraction and Environment Inference Based on Invariant Learning by Yujian Ding, Xiaoxu Ma, Bingxue Yang

“…This article proposes an image feature extraction algorithm based on invariant learning, which trains a ResNet18 model that can fully learn invariant features. …”
Get full text

Lane Detection Based on CycleGAN and Feature Fusion in Challenging Scenes by Eric Hsueh-Chan Lu, Wei-Chih Chiu

“…This paper proposes a novel method to train CycleGAN with existing daytime and nighttime datasets. …”
Get full text

Ensemble Learning-Based Person Re-identification with Multiple Feature Representations by Yun Yang, Xiaofang Liu, Qiongwei Ye, Dapeng Tao

Get full text

An Improved DGA Feature Clustering-Based Method for Transformer Fault Diagnosis by Yujie Zhang, Jian Feng, Shanyuan Wang

“…In order to solve those problems, this paper uses more features as information sources of power transformer diagnosis based on clustering method. …”
Get full text

Community evolution prediction based on feature change patterns in social networks by Jingyi Ding, Guojing Sun, Tiwen Wang, Licheng Jiao, Junzhao Du, Jianshe Wu, Hongfei Wang, Ruohui Cheng

“…This study proposes a community evolution prediction method based on feature change patterns, aiming to explore the changing features during community evolution, and designs an algorithm to learn the rules of feature changes, thereby obtaining the feature change pattern of the community. …”
Get full text

Evaluation of Human Action Based on Feature-Weighted Dynamic Time Warping by Mingdie Yan, Xia Liu, Zhaoyang Li, Naiyu Guo

“…The experimental results show that compared with the action evaluation method based on feature-matrix DTW, the proposed method significantly improves the similarity between healthy people and patients, and the similarity improvement for patients is more significant. …”
Get full text

Federated cross-view e-commerce recommendation based on feature rescaling by Ruiheng Li, Yuhang Shu, Yue Cao, Yiming Luo, Qiankun Zuo, Xuan Wu, Jiaojiao Yu, Wenxin Zhang

Get full text

Automatic crop type mapping based on crop-wise indicative features by Junru Yu, Longcai Zhao, Yanfu Liu, Qingrui Chang, Na Wang

“…The time series analysis method (i.e., seasonal trend decomposition) and imputation method was then utilized for the discrete time series of CIF extractors, which were separately trained based on training samples on each day. This process yielded the DCIF extractor that can capture the unique feature pattern on any given day during the entire growing period. …”
Get full text

Unsupervised Feature Representation Based on Deep Boltzmann Machine for Seizure Detection by Tengzi Liu, Muhammad Zohaib Hassan Shah, Xucun Yan, Dongping Yang

“…A novel unsupervised learning approach based on DBM, namely DBM_transient, is proposed by training DBM to a transient state for representing EEG signals in a 2D feature space and clustering seizure and non-seizure events visually. …”
Get full text