Improving the Algorithm for the Management of Patients with Viral Hepatitis Using Contrast-Free Hepatic Arterial Spin Labelling Magnetic Resonance Perfusion by E. N. Simakina, T. G. Morozova

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Pixel-wise navigation line extraction of cross-growth-stage seedlings in complex sugarcane fields and extension to corn and rice by Hongwei Li, Hongwei Li, Xindong Lai, Yongmei Mo, Deqiang He, Tao Wu, Tao Wu

“…In response to such challenges, we proposed a generalizable navigation line extraction algorithm using classical image processing technologies. …”
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Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

“…Geometric image transformations are fundamental to image processing, computer vision and graphics, with critical applications to pattern recognition and facial identification. …”
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Reducing the dynamic range of infrared images based on block-priority equalization and compression of histograms by S. I. Rudikov, V. Yu. Tsviatkou, A. P. Shkadarevich

“…When changing the ratio of the number of high-priority blocks of infrared image pixels to the number of all blocks in the range of 0.25–0.75, the proposed algorithm is more efficient than global and adaptive histogram equalization algorithms.…”
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Cloud Removal Advances: A Comprehensive Review and Analysis for Optical Remote Sensing Images by Jin Ning, Lianbin Xie, Jie Yin, Yiguang Liu

“…This phenomenon has made cloud removal a critical preprocessing step in ORS image processing. This article comprehensively reviews cloud removal techniques and classifies them based on the type of auxiliary data used: single-image, multimodal, and multitemporal. …”
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Predicting sensory evaluation of spinach freshness using machine learning model and digital images. by Kento Koyama, Marin Tanaka, Byeong-Hyo Cho, Yusaku Yoshikawa, Shige Koseki

“…Herein, the ability of an image processing-based, nondestructive technique to classify spinach freshness was evaluated. …”
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Computational Techniques for Analysis of Thermal Images of Pigs and Characterization of Heat Stress in the Rearing Environment by Maria de Fátima Araújo Alves, Héliton Pandorfi, Rodrigo Gabriel Ferreira Soares, Gledson Luiz Pontes de Almeida, Taize Calvacante Santana, Marcos Vinícius da Silva

“…The image analysis consisted of its pre-processing, followed by color segmentation to isolate the region of interest and later the extraction of the animal’s surface temperatures, from a developed algorithm and later the recognition of the comfort pattern through machine learning. …”
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Automatic Monitoring of Rock‐Slope Failures Using Distributed Acoustic Sensing and Semi‐Supervised Learning by Jiahui Kang, Fabian Walter, Patrick Paitz, Johannes Aichele, Pascal Edme, Lorenz Meier, Andreas Fichtner

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Research on Soil Pore Segmentation of CT Images Based on MMLFR-UNet Hybrid Network by Changfeng Qin, Jie Zhang, Yu Duan, Chenyang Li, Shanzhi Dong, Feng Mu, Chengquan Chi, Ying Han

“…This paper proposes a hybrid model combining a Multi-Modal Low-Frequency Reconstruction algorithm (MMLFR) and UNet (MMLFR-UNet). MMLFR enhances the key feature expression by extracting the image low-frequency signals and suppressing the noise interference through the multi-scale spectral decomposition, whereas UNet excels in the segmentation detail restoration and complexity boundary processing by virtue of its coding-decoding structure and the hopping connection mechanism. …”
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Industrial Computed Tomography Image Denoising Network Based on Channel Attention Mechanism by Yu HE, Chengxiang WANG, Wei YU

“…When the quality of projection data is poor, classical denoising and reconstruction algorithms are ineffective in removing the noise. To improve the quality of low signal-to-noise CT reconstructed images, this study proposes a deep learning-based denoising method. …”
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Texture Analysis and Classification using Local Binary Patterns and Statistical Features by Hasan Maher

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Color correction methods for underwater image enhancement: A systematic literature review. by Yong Lin Lai, Tan Fong Ang, Uzair Aslam Bhatti, Chin Soon Ku, Qi Han, Lip Yee Por

“…Physical model-based methods aim to reverse the effects of underwater image degradation by simulating the physical processes of light attenuation and scattering. …”
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A Non-Uniformity Correction Method for Uncooled Infrared Polarization Imaging Systems by Cailing Zhao, Zhiguo Fan, Yunxiang Zhang

“…However, due to the absence of a cold screen, such systems are susceptible to non-uniform internal thermal radiation exchange, which manifests as fixed pattern noise (FPN) independent of the scene during imaging. Previous non-uniformity correction (NUC) algorithms usually couple polarization information with FPN correction, resulting in the loss of polarization characteristics. …”
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Robust and Unified Semi-Supervised Unmixing of Hyperspectral Imaging for Linear and Multilinear Models by Daniel Ulises Campos-Delgado, Juan Nicolas Mendoza-Chavarria, Omar Gutierrez-Navarro, Laura Quintana-Quintana, Raquel Leon, Samuel Ortega, Himar Fabelo, Carlos Lopez, Marylene Lejeune, Gustavo M. Callico

“…The spectral unmixing paradigm is an important analysis tool for hyperspectral (HS) images which allows one to decompose the 2D spatial information from the basic spectral signatures or end-members. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…A novel approach, designated YOLOv8-POS, is introduced to address the issue of false detections in coal-rock image recognition tasks, frequently caused by factors such as image defocus, dim lighting, and worker occlusion, and to further enhance the model’s accuracy and reduce its complexity. …”
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Development of Ai-Based Crop Quality Grading Systems using Image Recognition by Dusi Prerna, Sharma Pooja

“…This research makes a contribution to the solution of these challenges by proposing a novel and automated crop quality grading system based on the use of advanced image recognition techniques. It also integrate Convolutional Neural Networks (CNN), Transfer Learning, Support Vector Machines (SVM) and Random Forest algorithms to label crop images into pre defined categories. …”
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High-content screening (HCS) workflows for FAIR image data management with OMERO by Riccardo Massei, Wibke Busch, Beatriz Serrano-Solano, Matthias Bernt, Stefan Scholz, Elena K. Nicolay, Hannes Bohring, Jan Bumberger

“…Abstract High-content screening (HCS) for bioimaging is a powerful approach to studying biological processes, enabling the acquisition of large amounts of images from biological samples. …”
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Application of Quantitative Interpretability to Evaluate CNN-Based Models for Medical Image Classification by Nuan Cui, Yingjie Wu, Guojiang Xin, Jiaze Wu, Liqin Zhong, Hao Liang

“…Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. …”
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Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…The rapid development of deep learning technology, especially the introduction of self-attention Transformer models, has greatly improved the accuracy of cloud detection tasks while achieving efficient processing of large-scale remote sensing images. This review provides a comprehensive overview of cloud detection algorithms based on deep learning from the perspective of semantic segmentation, and elaborates on the research progress, advantages, and limitations of different categories in this field. …”
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A Comparative Study of Azure Custom Vision Versus Google Vision API Integrated into AI Custom Models Using Object Classification for Residential Waste by Cosmina-Mihaela Rosca, Adrian Stancu, Marius Radu Tănase

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