Development of a technique to identify μm-sized organic matter in asteroidal material: An approach using machine learning by Rahul Kumar, Katsura Kobayashi, Christian Potiszil, Tak Kunihiro

“…The workflow involved image processing and machine learning, enabling a comprehensive and non-biased way of identifying, classifying, and measuring the properties of OM. …”
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3D modelling and x-ray depth analysis map of the pulp with computer software via digital periapical radiography and cone beam computed tomography by Turgut Felek, Samed Satir, Selale Ozel, H. Kursat Celik

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Development of an Algorithm for Semantic Segmentation of Earth Remote Sensing Data to Determine Phytoplankton Populations by Yu. V. Belova, I. F. Razveeva, E. O. Rakhimbaeva

“…The set of remote sensing images was supplemented with the author's augmentation algorithm in Python. …”
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Scanning SQUID microscope system for geological samples: further system improvements and development of post-processing software by Hirokuni Oda, Jun Kawai, Miki Kawabata, Naoto Fukuyo, Akihiro Tanimito, Isao Yosano, Chisato Anai

“…Additionally, the post-processing software has been developed. Various drift correction algorithms provide flexibility to the operator to deal with the situation including a narrow marginal area or a dirty marginal area contaminated with magnetic materials. …”
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Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images by Mahsa Raisi-Nafchi, Mahnoosh Tajmirriahi, Hossein Rabbani, Zahra Amini

“…This paper presents a new preoperative classification method for astrocytomas, addressing the issue of data scarcity in medical imaging. This work leverages an advanced statistical modeling approach based on stochastic differential equations to analyze post-contrast T1-weighted brain MRI images that require minimal data and offer rapid processing times. …”
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Speckle Noise Removal in OCT Images via Wavelet Transform and DnCNN by Fangfang Li, Qizhou Wu, Bei Jia, Zhicheng Yang

“…The Sobel, Prewitt, and Canny operators were utilized for edge detection on images, which validated the enhancement effect of the proposed algorithm on image edges. (4) Conclusions: The proposed algorithm in this paper exhibits an exceptional performance in noise suppression and detail preservation, demonstrating its potential application in OCT image denoising. …”
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Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling by Mrudul Jambulkar, Shivam Ojha, Amit Shelke, Anowarul Habib

“…The K-means algorithm enables precise localization and sizing of surface defects without prior labels, while the gamma process captures the stochastic progression of damage over time. …”
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Extracting Filaments Based on Morphology Components Analysis from Radio Astronomical Images by M. Zhu, W. Liu, B. Y. Wang, M. F. Zhang, W. W. Tian, X. C. Yu, T. H. Liang, D. Wu, D. Hu, F. Q. Duan

“…Removing tiny structures based on local information might remove some part of the filaments because filaments in radio astronomical image are usually weak. In order to solve this problem, we applied morphology components analysis (MCA) to process each singe spatial scale image and proposed a filaments extraction algorithm based on MCA. …”
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UAV image analysis for detecting rice seedling gaps and gap effect on grain yield by Sanai Li, Yubin Yang, Jing Zhang, Lloyd T. (Ted) Wilson, Stanley Omar P.B. Samonte, Fugen Dou, Tanumoy Bera, Xin-Gen Zhou, Darlene Sanchez, Jing Wang

“…Image processing algorithms were developed to extract plot and row lines from UAV images, enabling the estimation of gaps between rice seedlings within rows. …”
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Parallel Encryption of Noisy Images Based on Sequence Generator and Chaotic Measurement Matrix by Jiayin Yu, Yaqin Xie, Shiyu Guo, Yanqi Zhou, Erfu Wang

“…In the actual research process, the existing image encryption technology needs to be applied to the hardware. …”
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Dataset creation of thermal images of pomegranate for internal defect detectionMendeley Data by Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole

“…This information is useful for training a machine learning algorithms that are intended for bulk processing in the field of fruit defect detection and classification.…”
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Automated recognition and segmentation of lung cancer cytological images based on deep learning. by Qingyang Wang, Yazhi Luo, Ying Zhao, Shuhao Wang, Yiru Niu, Jinxi Di, Jia Guo, Guorong Lan, Lei Yang, Yu Shan Mao, Yuan Tu, Dingrong Zhong, Pei Zhang

“…Thus, in this study, we developed a model for intraoperative cytological segmentation of pulmonary lesions based on the YOLOv8 algorithm, which labels each instance by segmenting the image at the pixel level. …”
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Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning by Ickbum Kim, Sandeep Singh

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Two-Step CNN Framework for Text Line Recognition in Camera-Captured Images by Yulia S. Chernyshova, Alexander V. Sheshkus, Vladimir V. Arlazarov

“…Thus, the proposed solution is based on two separate artificial neural networks (ANN) and dynamic programming instead of employing image processing methods for the segmentation step or end-to-end ANN. …”
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A new method for voxelizing mesh phantoms through cross-sectional images by Raniele Costa de Matos dos Santos, Whoody Alem Wanderley Araripe Farias, José Wilson VIEIRA, Pedro Henrique Avelino de ANDRADE, Jefferson Melo Gonçalves PENA, Vanildo Júnior de Melo LIMA, Fernando Roberto de Andrad LIMA

“…To couple BREP phantoms with MC codes, GDN developed a method that converts polygonal meshes into voxels. This process is carried out using the in-house software DIP (Digital Image Processing), which converts mesh.obj files into voxels.sgi (Interactive Graphics Simulations). …”
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ODIASP: An Open‐Source Software for Automated SMI Determination—Application to an Inpatient Population by Katia Charrière, Antoine Ragusa, Béatrice Genoux, Antoine Vilotitch, Svetlana Artemova, Charlène Dumont, Paul‐Antoine Beaudoin, Pierre‐Ephrem Madiot, Gilbert R. Ferretti, Ivan Bricault, Eric Fontaine, Jean‐Luc Bosson, Alexandre Moreau‐Gaudry, Joris Giai, Cécile Bétry

“…ODIASP combines two algorithms to automate L3 slice selection and skeletal muscle segmentation, ensuring a seamless process. …”
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Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective by Ying Huey Gan, Shih Yin Ooi, Ying Han Pang, Yi Hong Tay, Quan Fong Yeo

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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“… The study is dedicated to the problem of classification of structural and functional development stage of cardiomyocytes derived from the induced pluripotent stem cells with application of the digital image processing methods and machine learning algorithms, in particular, neural networks. …”
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Engineered feature embeddings meet deep learning: A novel strategy to improve bone marrow cell classification and model transparency by Jonathan Tarquino, Jhonathan Rodríguez, David Becerra, Lucia Roa-Peña, Eduardo Romero

“…This assessment is still manually performed by trained specialists, who may be a bottleneck within the clinical process. Deep learning algorithms are a promising approach to automate this bone marrow cell evaluation. …”
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