Statistical modeling based fast rate estimation algorithm for VVC by Wei QI, Haibing YIN, Hongkui WANG, Xiaofeng HUANG, Weihong NIU

“…To reduce the coding complexity of the rate-distortion optimization process of the latest video coding standard versatile video coding (VVC), a fast rate estimation model based on statistical modeling was proposed.Firstly, the quantization behavior in dependent quantization (DQ) and the context dependency in entropy coding were fully considered.Features that could describe context state transition in the coding process were proposed to estimate rate of some synatax elements in a TU preliminarily.Secondly, coefficient chaos and sparsity features were proposed to distinguish the influence of coefficient distribution difference on the rate cost based on the coefficient distribution characteristics which built a TU level rate model.Finally, large-size transform unit (TU) and small-size TU was modeling respectively according to the rate composition character to achieve more accurate rate estimation.A large number of parameters were trained by regression model through statistical methods, and the final linear rate model was obtained which was applied to the mode decision.Experimental results show that the proposed algorithm can achieve 16.289% complexity reduction with 1.567% BD-BR increase for RA configuration.…”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

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Small-Target Detection Algorithm Based on STDA-YOLOv8 by Cun Li, Shuhai Jiang, Xunan Cao

“…Due to the inherent limitations of detection networks and the imbalance in training data, small-target detection has always been a challenging issue in the field of target detection. …”
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Automatic serving method of volleyball training robot based on improved YOLOv5 and improved Hough transform by Tao Sun, Xiaolong He, Jiajun Zhang

“…An automatic serving method for volleyball training robots is proposed based on You Only Look Once v5 and Hough transform. …”
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Winter Wheat Canopy Height Estimation Based on the Fusion of LiDAR and Multispectral Data by Hao Ma, Yarui Liu, Shijie Jiang, Yan Zhao, Ce Yang, Xiaofei An, Kai Zhang, Hongwei Cui

“…Therefore, a method is proposed that fuses LiDAR point cloud features and multispectral feature parameters to estimate the canopy height of winter wheat. …”
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Stone inscription image segmentation based on Stacked-UNets and GANs by Pan Zhang, Chao Li, Yuanhua Sun

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Generative AI-Based Platform for Deliberate Teaching Practice: A Review and a Suggested Framework by Yehudit Aperstein, Yuval Cohen, Alexander Apartsin

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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

“…To address this issue, this study employs a One-Class Support Vector Machine (OCSVM) trained exclusively on features extracted from healthy brain MRI images, using both deep learning architectures—such as DenseNet121, VGG16, MobileNetV2, InceptionV3, and ResNet50—and classical feature extraction techniques. …”
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Radar HRRP recognition based on supervised exponential sparsity preserving projection with small training data size by X. Yang, G. Zhang, H. Song

“…Experimental results on measured radar data demonstrate that the proposed method effectively reduces feature dimensionality and enhances target recognition performance with limited training data.…”
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Group-based siamese self-supervised learning by Zhongnian Li, Jiayu Wang, Qingcong Geng, Xinzheng Xu

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Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters by BAI Jinlei, WANG Yue, JIANG Fan, ZHANG Zhengfang, SHI Ke, ZHONG Puhua

“…Its key technical feature lies in a new safety braking model developed based on the concept of "dynamic tracking". …”
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Home-based transcranial direct current stimulation paired with cognitive training to reduce fatigue in multiple sclerosis by Leigh Charvet, Judith D. Goldberg, Xiaochun Li, Pamela Best, Matthew Lustberg, Michael Shaw, Lana Zhovtis, Josef Gutman, Abhishek Datta, Marom Bikson, Giuseppina Pilloni, Lauren Krupp

“…We conducted a double-blind, sham-controlled, randomized clinical trial to compare active vs. low-dose (sham) tDCS paired with computer-based cognitive training, delivered as a home-based intervention, to reduce MS-related fatigue. …”
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Transfer Learning Model for Crack Detection in Side SlopesBased on Crack-Net by Na Li, Yilong Zhang, Qing Zhang, Shaoguang Zhu

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Features of the formation of vocal and stage skills among students of Chinese universities in the process of learning opera singing by He Chang, Natalya G. Tagiltseva

“…The article attempts to identify the features of opera performance training in bachelor's degree programs in higher educational institutions in China, where the process of formation of vocal and stage skills occupies a central place. …”
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ATTRIBUTION OF MEDIA TEXTS BASED ON A TRAINED NATURAL LANGUAGE MODEL AND LINGUISTIC ASSESSMENT OF IDENTIFICATION QUALITY by Vladimir A. Klyachin, Ekaterina V. Khizhnyakova

“…The article presents the results of automatic detection of high-quality media texts, as well as text samples with infodemic features carried out using a trained natural language model based on a manually labeled corpus. …”
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StomaYOLO: A Lightweight Maize Phenotypic Stomatal Cell Detector Based on Multi-Task Training by Ziqi Yang, Yiran Liao, Ziao Chen, Zhenzhen Lin, Wenyuan Huang, Yanxi Liu, Yuling Liu, Yamin Fan, Jie Xu, Lijia Xu, Jiong Mu

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Model of recreational and training sessions based on the use of funds aqua professionally applied in the preparation of students of economics by N. V. Petrenko, T. A. Loza

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DYNAMIC UNBALANCE DETECTION OF CARDAN SHATF IN HIGH-SPEED TRAIN BASED ON MODIFIED VARIATIONAL MODE DECOMPOSITION by HONG JianFeng, DING JianMing, LIN JianHui, ZHENG ShuBin

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A generative model-based coevolutionary training framework for noise-tolerant softsensors in wastewater treatment processes by Yu Peng, Erchao Li

“…However, the effectiveness of softsensor models is often hindered by noise in data acquisition, posing significant challenges for model training. To tackle this issue, this study introduces a coevolutionary training framework based on generative models to mitigate the impact of noise corruption. …”
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A Mathematical Method for Predicting Tunnel Pressure Waves Based on Train Wave Signature and Graph Theory by Xu Zhang, Haiquan Bi, Honglin Wang, Yuanlong Zhou, Nanyang Yu, Jizhong Yang, Yao Jiang

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