Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Finally, conducted a visualization analysis of the detection boxes and central heatmaps. …”
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Semantic knowledge graph fusion for fake news detection: Unifying content-based features and evidence-based analysis in the COVID-19 infodemic. by Rayees Ahmad Dar, Rana Hashmy, Muhammad Shahid Anwar, Patrik Böhm, Jaroslav Frnda

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Infrared Moving Small Target Detection Based on Spatial–Temporal Feature Fusion Tensor Model by Deyong Lu, Wei An, Haibo Wang, Qiang Ling, Dong Cao, Miao Li, Zaiping Lin

“…Infrared moving small target detection is an important and challenging task in infrared search and track system, especially in the case of low signal-to-clutter ratio (SCR) and complex scenes. …”
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Back Propagation Neural Network model for analysis of hyperspectral images to predict apple firmness by Shuiping Li, Yueyue Chen, Xiaobo Zhang, Junbo Wang, Xuanxiang Gao, Yunhong Jiang, Zhaojun Ban, Cunkun Chen

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Approach of detecting low-rate DoS attack based on combined features by Zhi-jun WU, Jing-an ZHANG, Meng YUE, Cai-feng ZHANG

“…LDoS (low-rate denial of service) attack is a kind of RoQ (reduction of quality) attack which has the characteristics of low average rate and strong concealment.These characteristics pose great threats to the security of cloud computing platform and big data center.Based on network traffic analysis,three intrinsic characteristics of LDoS attack flow were extracted to be a set of input to BP neural network,which is a classifier for LDoS attack detection.Hence,an approach of detecting LDoS attacks was proposed based on novel combined feature value.The proposed approach can speedily and accurately model the LDoS attack flows by the efficient self-organizing learning process of BP neural network,in which a proper decision-making indicator is set to detect LDoS attack in accuracy at the end of output.The proposed detection approach was tested in NS2 platform and verified in test-bed network environment by using the Linux TCP-kernel source code,which is a widely accepted LDoS attack generation tool.The detection probability derived from hypothesis testing is 96.68%.Compared with available researches,analysis results show that the performance of combined features detection is better than that of single feature,and has high computational efficiency.…”
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SPECIFIC FEATURES OF NON-TUBERCULOUS PULMONARY DISEASES DETECTION IN TB HOSPITALS by Z. A. Laushkina, V. A. Krasnov

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Detecting Driver Drowsiness Using Hybrid Facial Features and Ensemble Learning by Changbiao Xu, Wenhao Huang, Jiao Liu, Lang Li

“…To address these issues, we propose a drowsiness detection method that combines an ensemble model with hybrid facial features. …”
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Can behavioral features reveal lying in an online personality questionnaire? The impact of mouse dynamics and speech by Eduard Kuric, Peter Demcak, Peter Smrecek, Stefan Benus

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CWCM-Net: A Novel Feature Fusion Method for Oil Spill Detection Using Single- and Quad-Polarization SAR Data by Sohail Jamal, Guangmin Sun, Yu Li, Abdul Qadir Khan, Yuanzhi Zhang, Anna Verlanti, Ferdinando Nunziata

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Spectroscopic detection of cotton Verticillium wilt by spectral feature selection and machine learning methods by Weinan Li, Weinan Li, Weinan Li, Lisen Liu, Jianing Li, Weiguang Yang, Weiguang Yang, Yang Guo, Yang Guo, Longyu Huang, Longyu Huang, Zhaoen Yang, Jun Peng, Jun Peng, Xiuliang Jin, Xiuliang Jin, Yubin Lan, Yubin Lan

“…Initial analysis identified critical spectral reflectance bands, wavelet coefficients, and SIs that exhibited dynamic responses as the disease progressed.ResultsModel validation demonstrated that the incidence detection models at the leaf scale achieved a peak classification accuracy of 85.83%, which is about 10% higher than traditional methods without feature selection. …”
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Optimizing Fire Scene Analysis: Hybrid Convolutional Neural Network Model Leveraging Multiscale Feature and Attention Mechanisms by Shakhnoza Muksimova, Sabina Umirzakova, Mirjamol Abdullaev, Young-Im Cho

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A hybrid deep learning framework for early detection of Mpox using image data by Sajal Chakroborty

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A Method to Detect Concealed Damage in Concrete Tunnels Using a Radar Feature Vector and Bayesian Analysis of Ground-Penetrating Radar Data by Junfang Wang, Heng Chen, Jianfu Lin, Xiangxiong Li

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Automated Seedling Contour Determination and Segmentation Using Support Vector Machine and Image Features by Samsuzzaman, Md Nasim Reza, Sumaiya Islam, Kyu-Ho Lee, Md Asrakul Haque, Md Razob Ali, Yeon Jin Cho, Dong Hee Noh, Sun-Ok Chung

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Class-weighted Dempster–Shafer in dual-level fusion for multimodal fake real estate listings detection by Maifuza Mohd Amin, Nor Samsiah Sani, Mohammad Faidzul Nasrudin

“…This underscores the potential of integrating multimodal analysis with sophisticated fusion techniques to enhance the detection of fake property listings, ultimately improving consumer protection and operational efficiency in online real estate platforms.…”
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Smartphone sensor-based depression detection in campus environments: a proof-of-concept study with small-sample behavioral analysis by Yichen Bai, Yueze Liu, Yang Zhang, Amr Tolba

Subjects: “…depression detection…”
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A review of deep learning in blink detection by Jianbin Xiong, Weikun Dai, Qi Wang, Xiangjun Dong, Baoyu Ye, Jianxiang Yang

“…Compared with traditional methods, the blink detection method based on deep learning offers superior feature learning ability and higher detection accuracy. …”
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N6-methyladenine identification using deep learning and discriminative feature integration by Salman Khan, Islam Uddin, Sumaiya Noor, Salman A. AlQahtani, Nijad Ahmad

“…To optimize computational efficiency and eliminate irrelevant or noisy features, an unsupervised Principal Component Analysis (PCA) algorithm is employed, ensuring the selection of the most informative features. …”
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Music Classification and Detection of Location Factors of Feature Words in Complex Noise Environment by Yulan Xu, Qiaowei Li

“…In order to solve the problem of the influence of feature word position in lyrics on music emotion classification, this paper designs a music classification and detection model in complex noise environment. …”
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A Spatiotemporal Feature-Based Approach for the Detection of Unlicensed Taxis in Urban Areas by Yun Xiao, Rongqiao Li, Jinyan Li

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