A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization by Mădălina Duceac (Covrig), Călin Gheorghe Buzea, Alina Pleșea-Condratovici, Lucian Eva, Letiția Doina Duceac, Marius Gabriel Dabija, Bogdan Costăchescu, Eva Maria Elkan, Cristian Guțu, Doina Carina Voinescu

“…Predicting recurrence after lumbar disc herniation (LDH) remains clinically important but algorithmically difficult due to extreme class imbalance and low signal-to-noise ratio. …”
Get full text

The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification by Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang

Get full text

Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…The direction for further research is to improve the ant algorithm.…”
Get full text

Optimal fuzzy-PID controller design for object tracking by Yaregal Limenih Melese, Girma Kassa Alitasb, Mequanent Degu Belete

“…Genetic algorithm (GA) was used to find the optimal values of the operating ranges (scaling factors) of the membership functions. …”
Get full text

High‐Impedance Fault Detection in Distribution Networks Based on Support Vector Machine and Wavelet Transform Approach (Case Study: Markazi Province of Iran) by Mohammad Sadegh Attar, Mohammad Reza Miveh

“…This paper employs a support vector machine (SVM) classification algorithm that demonstrates reliable accuracy and discrete wavelet transform (DWT) in HIF detection. …”
Get full text

A data-efficient deep transfer learning framework for methane super-emitter detection in oil and gas fields using the Sentinel-2 satellite by S. Zhao, S. Zhao, Y. Zhang, Y. Zhang, S. Zhao, S. Zhao, X. Wang, X. Wang, D. J. Varon

“…Here, we propose a novel deep-transfer-learning-based methane plume detection framework. It consists of two components: an adaptive artifact removal algorithm (low-reflectance artifact detection, LRAD) to reduce artifacts in methane retrievals and a deep subdomain adaptation network (DSAN) to detect methane plumes. …”
Get full text

Detection of Pesticide Residues Using Three-Dimensional SERS Substrate Based on CNTs/Ag/AgNWs/SiO₂ by Jianjun Ding, Niansong Liu, Ganglin Wang, Naiyu Guo, Chao Sun

“…In response to the shortcomings of traditional surface-enhanced Raman spectroscopy (SERS) substrates, such as short shelf life, poor uniformity, and low selectivity, this study innovatively proposed a three-dimensional composite substrate of CNTs/Ag/AgNWs/SiO₂. …”
Get full text

Research on Detection of Icing Cover Transmission Lines Under Different Weather Conditions Based on Wide-Field Dynamic Convolutional Network LDKA-NET by Xinsheng Dong, Yuanhao Wan, Yongcan Zhu, Chao Ji

“…To address the issue of low detection accuracy for icing transmission line defects with existing models, this paper proposes a defect detection algorithm for icing transmission line defects under different weather conditions based on a Large Dynamic Kernel Aggregation Net (LDKA-NET). …”
Get full text

LittleFaceNet: A Small-Sized Face Recognition Method Based on RetinaFace and AdaFace by Zhengwei Ren, Xinyu Liu, Jing Xu, Yongsheng Zhang, Ming Fang

“…For surveillance video management in university laboratories, issues such as occlusion and low-resolution face capture often arise. Traditional face recognition algorithms are typically static and rely heavily on clear images, resulting in inaccurate recognition for low-resolution, small-sized faces. …”
Get full text

Dynamic Bearing–Angle for Vision-Based UAV Target Motion Analysis by Yu Luo, Hongwei Fu, Tingting Fu, Hao Cha, Bing Tian, Huatao Tang, Feng Liu

“…The Bearing–Angle algorithm effectively improves the observability of vision-based motion estimation for moving targets by combining the dimensional information of target detection frames. …”
Get full text

Advanced Cotton Boll Segmentation, Detection, and Counting Using Multi-Level Thresholding Optimized with an Anchor-Free Compact Central Attention Network Model by Arathi Bairi, Uma N. Dulhare

“…There are limited techniques developed to segment, detect, and count cotton bolls precisely. This analysis identified several limitations and issues with these techniques, including their complex structure, low performance, time complexity, poor quality data, and so on. …”
Get full text

Multi-Channel Fusion Decision-Making Online Detection Network for Surface Defects in Automotive Pipelines Based on Transfer Learning VGG16 Network by Jian Song, Yingzhong Tian, Xiang Wan

“…Although approaches for the online surface detection of automotive pipelines exist, low defect area rates, small-sample and long-tailed data, and the difficulty of detection due to the variable morphology of defects are three major problems faced when using such methods. …”
Get full text

Multi-View Robust Tensor-Based Subspace Clustering by Esraa M. Al-Sharoa, Mohammad A. Al-Wardat

Get full text

Securing IoT devices with zero day intrusion detection system using binary snake optimization and attention based bidirectional gated recurrent classifier by Ali Saeed Almuflih, Ilyos Abdullayev, Sergey Bakhvalov, Rustem Shichiyakh, Bibhuti Bhusan Dash, K. B. V. Brahma Rao, Kritika Bansal

“…This manuscript presents a Binary Snake Optimizer with DL-Enabled Zero-Day Attack Detection and Classification (BSODL-ZDADC) method. …”
Get full text

Detection of Parabolic Antennas in Satellite Inverse Synthetic Aperture Radar Images Using Component Prior and Improved-YOLOv8 Network in Terahertz Regime by Liuxiao Yang, Hongqiang Wang, Yang Zeng, Wei Liu, Ruijun Wang, Bin Deng

“…In order to tackle the challenges associated with component identification in satellite ISAR imagery, this study employs the Improved-YOLOv8 model, which was developed by incorporating the YOLOv8 algorithm, an adaptive detection head known as the Dynamic head (Dyhead) that utilizes an attention mechanism, and a regression box loss function called Wise Intersection over Union (WIoU), which addresses the issue of varying sample difficulty. …”
Get full text

Clinical, Echocardiographic and Laboratory Cardiac Monitoring in Breast Cancer Patients Undergoing Chemotherapy with Anthracycline Agents: A Pilot Study on Cardioprotective Algorit... by Indah Puspita

Get full text

High-roubustness keystroke recognition method based on acoustic spatial gradient by Ying LIU, Kangkang HAN, Zhihong QIAN

“…For the fluctuation of CFCC caused by environmental noise is the main reason for the low accuracy of keystroke detection,the spatial characteristics of adjacent between CFCC were studied,and the spatial gradient structure of CFCC based on points was established.On this basis,the effect of CFCC spatial gradient on keystroke content recognition and the selection of precise neighborhood points were studied on training and testing.Finally,a high-robustness keystroke recognition algorithm based on acoustic signals was constructed.Extensive experiments in different environments demonstrate that the proposed CFCC spatial gradient sound feature achieves great performance and the recognition accuracy is 96.15%.…”
Get full text

Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

Get full text

High-roubustness keystroke recognition method based on acoustic spatial gradient by Ying LIU, Kangkang HAN, Zhihong QIAN

“…For the fluctuation of CFCC caused by environmental noise is the main reason for the low accuracy of keystroke detection,the spatial characteristics of adjacent between CFCC were studied,and the spatial gradient structure of CFCC based on points was established.On this basis,the effect of CFCC spatial gradient on keystroke content recognition and the selection of precise neighborhood points were studied on training and testing.Finally,a high-robustness keystroke recognition algorithm based on acoustic signals was constructed.Extensive experiments in different environments demonstrate that the proposed CFCC spatial gradient sound feature achieves great performance and the recognition accuracy is 96.15%.…”
Get full text

Research on Fault Diagnosis of Chillers Based on Improved BP Network by Shi Shubiao, Chen Huanxin, Li Guannan, Hu Yunpeng, Li Haorong, Hu Wenju, Li Jiong

“…The overall detection rate using conventional neural networks to detect and diagnose the chillers’ fault is low, even this method can’t detect the fault completely. …”
Get full text