A Driver Behavior Detection Model for Human-Machine Co-Driving Systems Based on an Improved Swin Transformer by Junhua Cui, Yunxing Chen, Zhao Wu, Huawei Wu, Wanghao Wu

Get full text

Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…The simple Chinese word characteristics in the fourth layer are more abundant than in the fifth, whereas complex handwritten Chinese words contain similarly detailed features across both layers.Results and DiscussionsThe training image datasets for the experiment consist of two groups. …”
Get full text

FEATURES OF AN ESTIMATION OF INVESTMENT PROJECTS AT THE ENTERPRISES OF AVIATION INSTRUMENT by Petr P. Dobrov

Get full text

Detection of network intelligence features with the decision tree model by N. P. Sharaev, S. N. Petrov

“…The study was carried out to develop software module for detecting the features of network intelligence by machine learning methods.M e t h o d s . …”
Get full text

Features of marketing for educational services of higher education institution by T.A. Yashchuk

Get full text

CLIP-Llama: A New Approach for Scene Text Recognition with a Pre-Trained Vision-Language Model and a Pre-Trained Language Model by Xiaoqing Zhao, Miaomiao Xu, Wushour Silamu, Yanbing Li

“…The visual branch provides initial predictions based on image features, while the cross-modal branch refines these predictions by addressing the differences between image features and textual semantics. …”
Get full text

Professional Features of IT Specialists’ Activities as Burnout Risk Factors by Alena F. Dzhumagulova, Natalia E. Vodopyanova, Olga O. Gofman, German S. Nikiforov

“…The interview and the questionnaire covered 19 and 82 IT experts, respectively. Based on the analysis of the obtained data, the authors were able to determine: (1) the job duties of representatives of the professions of ‘programmer’, ‘analyst’ and ‘tester’; (2) the most common causes of professional errors in the IT sphere, as well as their consequences as risk factors for burnout; (3) the minimum level of training, educational requirements and criteria for success in activities; (4) the most common cognitive and social work operations of IT professions; (5) requirements for the level of health and working conditions, as well as possible occupational diseases; and (6) data on the imbalance of work and rest, work and personal life. …”
Get full text

Features of legal regulation of labor relation of aviation personnel by A. V. Zhyla, A. O. Hordeiuk

Get full text

Dermoscopic features in children with vitiligo and other hypopigmentation disorders by Shijuan Yu, Shijuan Yu, Jingyi He, Hua Wang

Get full text

Quantum-Inspired Multi-Scale Object Detection in UAV Imagery: Advancing Ultra-Small Object Accuracy and Efficiency for Real-Time Applications by Muhammad Muzammul, Muhammad Assam, Ayman Qahmash

Get full text

Short-term PV power prediction based on meteorological similarity days and SSA-BiLSTM by Yikang Li, Wei Huang, Keying Lou, Xizheng Zhang, Qin Wan

“…Firstly, the correlation between meteorological factors and PV power generation is calculated by using Pearson coefficients, getting the strongly correlated meteorological factors affecting PV power generation; afterwards,the historical data of the strongly correlated meteorological factors are clustered by fuzzy C-means clustering to achieve meteorological similar day clustering; then, the best similar day is selected from the meteorological similar day according to the test day seasonal features and meteorological data, and Forming a training set with historical data, and training the original BiLSTM network. the SSA algorithm was used to find the optimal BiLSTM network parameters. …”
Get full text

Spatial–Spectral Hierarchical Multiscale Transformer-Based Masked Autoencoder for Hyperspectral Image Classification by Haipeng Liu, Zhen Ye, Wen-Shuai Hu, Zhan Cao, Wei Li

“…Due to the excellent feature extraction capabilities, deep learning has become the mainstream method for hyperspectral image (HSI) classification. …”
Get full text

ETAFHrNet: A Transformer-Based Multi-Scale Network for Asymmetric Pavement Crack Segmentation by Chao Tan, Jiaqi Liu, Zhedong Zhao, Rufei Liu, Peng Tan, Aishu Yao, Shoudao Pan, Jingyi Dong

“…ETAFHrNet integrates Transformer-based global attention and multi-scale hybrid feature fusion, enhancing both contextual perception and detail sensitivity. …”
Get full text

A novel dynamic weighted prediction framework with stability-enhanced dynamic thresholding feature selection for neurodegenerative disease detection using gait features by Diksha Giri, Ranjit Panigrahi, Samrat Singh Bhandari, Moumita Pramanik, Akash Kumar Bhoi, Victor Hugo C. de Albuquerque

“…Unlike fixed threshold approaches, SEDT may adjust to different data subsets' feature relevance, preserving only the most important features for model training. …”
Get full text

Construction and validation of a risk stratification model based on Lung-RADS® v2022 and CT features for predicting the invasive pure ground-glass pulmonary nodules in China by Qingcheng Meng, Tong Liu, Hui Peng, Pengrui Gao, Wenda Chen, Mengjia Fang, Wentao Liu, Hong Ge, Renzhi Zhang, Xuejun Chen

“…Abstract Objectives A novel risk stratification model based on Lung-RADS® v2022 and CT features was constructed and validated for predicting invasive pure ground-glass nodules (pGGNs) in China. …”
Get full text

Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

Get full text

Grading evaluation method for inter-turn short circuit of permanent magnet traction motor based on deep Gaussian processes by DAI Jisheng, HU Dean, XU Hailong, ZHU Wenlong, LIAO Qishu

“…Therefore, this paper proposed a grading evaluation method for inter-turn short circuit in permanent magnet traction motors based on multi-feature fusion of deep Gaussian processes. …”
Get full text

PIPNet: A Deep Convolutional Neural Network for Multibaseline InSAR Phase Unwrapping Based on Pure Integer Programming by Hui Liu, Ke Zheng, Changwei Miao, Xuemei Liu, Xianlin Liu, Lin Li, Yongguang Zhang, Longhai Xiong

Get full text

A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders by Jorge Magalhães, Tomás Jorge, Rúben Silva, António Guedes, Diogo Ribeiro, Andreia Meixedo, Araliya Mosleh, Cecília Vale, Pedro Montenegro, Alexandre Cury

“…The proposed procedure is based on a machine learning methodology and includes the following stages: (1) data collection, (2) damage-sensitive feature extraction from the acquired responses using a neural network model, i.e., the sparse autoencoder (SAE), (3) data fusion based on the Mahalanobis distance, and (4) unsupervised feature classification by implementing outlier and cluster analysis. …”
Get full text

Application value of dual-sequence MRI based nomogram of radiomics and morphologic features in predicting tumor differentiation degree and lymph node metastasis of Oral squamous ce... by Bozhong Zheng, Baoting Yu, Xuewei Zheng, Xiaolong Qu, Tong Li, Yun Zhang, Jun Ding

Get full text