Performance Evaluation of Some Selected Classification Algorithms in a Facial Recognition System by Michael Olumuyiwa Adio, Ogunmakinde Jimoh Ogunwuyi, Mayowa Oyedepo Oyediran, Adebimpe Omolayo Esan, Olufikayo Adepoju Adedapo

“…With the development of image processing and pattern recognition technology, there are many challenges in machine learning to select the appropriate classification algorithms, most especially in the area of classification of extracted features to have low classification time, high sensitivity and accuracy of the classification algorithms, so it is very important to explore the performance of different algorithms in image classification. …”
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Electrical Resistivity Tomography Methods and Technical Research for Hydrate-Based Carbon Sequestration by Zitian Lin, Qia Wang, Shufan Li, Xingru Li, Jiajie Ye, Yidi Zhang, Haoning Ye, Yangmin Kuang, Yanpeng Zheng

“…The experiments used boundary voltage as the input and internal conductivity distribution as the output, employing the relative image error (RIE) and image correlation coefficient (ICC) to evaluate algorithmic performance. …”
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Registration of the Cone Beam CT and Blue-Ray Scanned Dental Model Based on the Improved ICP Algorithm by Xue Mei, Zhenhua Li, Songsong Xu, Xiaoyan Guo

“…As the needs of the different resolution image registration, we develop an improved Iterative Closest Point (ICP) algorithm that focuses on the registration of Cone Beam Computed Tomography (CT) image and high-resolution Blue-light scanner image. …”
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Separable reversible data hiding by vacating room after encryption using encrypted pixel difference by Veeramuthu Venkatesh, R. Anushiadevi, Padmapriya Velupillai Meikandan, Hemalatha Mahalingam, Rengarajan Amirtharajan

“…It achieves an embedding rate of 1.2 bpp, significantly improving upon standard VRAE algorithms while allowing for lossless data extraction and image recovery. …”
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A Practical Methodology for Accuracy and Quality Evaluation of Structured Light Systems in Automotive Inspection by Antonio Lagudi, Umberto Severino, Loris Barbieri, Fabio Bruno

“…It also demonstrated the ability to quantify improvements obtained through image enhancement algorithms. These results confirm the methodology’s capacity to expose critical performance trade-offs and guide optimization choices in practical inspection scenarios. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…It contributes to the broader discourse on the potential of hybrid, randomization-inspired neural networks in medical imaging. This fusion of deep learning innovation with the principles of randomization-based algorithms opens new avenues for developing accessible, accurate diagnostic tools, potentially alleviating the global impact of diabetic vision loss.…”
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Model-Based Hardware-Software Codesign of ECT Digital Processing Unit by Atef Allam, Wael Deabes

“…Image reconstruction algorithm and its controller constitute the main modules of the electrical capacitance tomography (ECT) system; in order to achieve the trade-off between the attainable performance and the flexibility of the image reconstruction and control design of the ECT system, hardware-software codesign of a digital processing unit (DPU) targeting FPGA system-on-chip (SoC) is presented. …”
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Voltage-controlled magnetoelectric devices for neuromorphic diffusion process by Yang Cheng, Qingyuan Shu, Albert Lee, Haoran He, Ivy Zhu, Minzhang Chen, Renhe Chen, Zirui Wang, Hantao Zhang, Chih-Yao Wang, Shan-Yi Yang, Yu-Chen Hsin, Cheng-Yi Shih, Hsin-Han Lee, Ran Cheng, Kang L. Wang

“…We experimentally demonstrate that the hardware-based true random diffusion process can be implemented for image generation and achieve comparable image quality to software-based training as measured by the Fréchet inception distance (FID) score, achieving ~103 better energy-per-bit-per-area over traditional hardware.…”
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The Algorithm of Treatment Tactics for Patients with Tumor Obstruction of Extrahepatic Bile Ducts by Dutka Ya.

“…To work out an effective algorithm for treating the patients with pulmonary embolism taking into account age and general condition, localization, distribution and stage of the tumor process. …”
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Semantic processing of argument structure during naturalistic story listening: Evidence from computational modeling on fMRI by Tianze Xu, Jixing Li, Xiaoming Jiang

“…The methodological framework integrated a general linear model (GLM) analysis of the fMRI data with computational modeling using natural language processing algorithms. These components were integrated using representational similarity analysis (RSA), allowing us to assess the relatedness of two symbolic computational models—one relying on syntactic information from parse trees and the other based on semantic selectional preference information of verbs—to brain activities. …”
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Research on Beef Marbling Grading Algorithm Based on Improved YOLOv8x by Jun Liu, Lian Wang, Huafu Xu, Jie Pi, Daoying Wang

“…The model integrates a convolutional neural network (CNN) augmented with an improved attention mechanism and loss function, along with a Region-of-Interest (ROI) preprocessing algorithm to automate the marbling grading process. …”
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Cross-domain subcortical brain structure segmentation algorithm based on low-rank adaptation fine-tuning SAM by Yuan Sui, Qian Hu, Yujie Zhang

“…Methods This paper proposes a subcortical brain structure segmentation algorithm based on Low-Rank Adaptation (LoRA) to fine-tune SAM (Segment Anything Model) by freezing SAM’s image encoder and applying LoRA to approximate low-rank matrix updates to the encoder’s training weights, while also fine-tuning SAM’s lightweight prompt encoder and mask decoder. …”
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Multi‐sensor missile‐borne LiDAR point cloud data augmentation based on Monte Carlo distortion simulation by Luda Zhao, Yihua Hu, Fei Han, Zhenglei Dou, Shanshan Li, Yan Zhang, Qilong Wu

“…Firstly, the model of multi‐sensor imaging system is established, taking into account the joint errors arising from the platform itself and the relative motion during the imaging process. …”
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Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting by Jichang Zhang, Faisal Najeeb, Yulin Wang, Xinpei Wang, Pengfei Xu, Hammad Omer, Jianjun Zheng, Jingfeng Zhang, Sue Francis, Paul Glover, Richard Bowtell, Thomas Meersmann, Chengbo Wang

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A Simple Algorithm for Compensation for Range Cell Migration in a Stripmap SAR by A. A. Monakov

“…The conducted analysis showed that the algorithm yields  the  image of a moving target provided that the coherent processing interval is sufficiently large. …”
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Effect of crystal-to-detector distance shift on data processing in serial crystallography. by Ki Hyun Nam

“…The CTDD that yielded the maximum number of indexed images differed from the optimized CTDD, and the resulting indexing trends varied depending on the algorithm used. …”
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An Oil Painters Recognition Method Based on Cluster Multiple Kernel Learning Algorithm by Zhifang Liao, Le Gao, Tian Zhou, Xiaoping Fan, Yan Zhang, Jinsong Wu

“…A lot of image processing research works focus on natural images, such as in classification, clustering, and the research on the recognition of artworks (such as oil paintings), from feature extraction to classifier design, is relatively few. …”
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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

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Fog Visibility Detection of Highway Based on Improved Dark Channel Prior Algorithm by Huiqi Zhang, Yong Liu, Chenxi Wu

“…This paper presents an algorithm for detecting fog visibility in expressway based on improved dark channel prior method, which transforms the difficult problem of detecting visibility through image processing into the problem of calculating atmospheric extinction coefficient. …”
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CNN-based Gender Prediction in Uncontrolled Environments by Kazım Yıldız, Engin Güneş, Anil Bas

“…By using deep learning techniques from these technologies, high performance can be achieved in tasks such as classification and face analysis in the fields of image processing and computer vision. In this study, Convolutional Neural Networks (CNN), one of the deep learning algorithms, was used. …”
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