Optimal Res-UNET architecture with deep supervision for tumor segmentation by Rahman Maqsood, Fazeel Abid, Jawad Rasheed, Jawad Rasheed, Jawad Rasheed, Onur Osman, Shtwai Alsubai

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Automatic Tissue Differentiation in Parotidectomy using Hyperspectral Imaging by Wisotzky Eric L., Schill Alexander, Hilsmann Anna, Eisert Peter, Knoke Michael

“…In head and neck surgery, continuous intraoperative tissue differentiation is of great importance to avoid injury to sensitive structures such as nerves and vessels. Hyperspectral imaging (HSI) with neural network analysis could support the surgeon in tissue differentiation. …”
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Comparative geographical analysis of student mental maps of Stavropol and Pyatigorsk by E. I. Vinogradova, G. N. Zhirenko, I. P. Suprunchuk, P. M. Polyan

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Prediction of the Next Solar Rotation Synoptic Maps Using an Artificial Intelligence–based Surface Flux Transport Model by Hyun-Jin Jeong, Mingyu Jeon, Daeil Kim, Youngjae Kim, Ji-Hye Baek, Yong-Jae Moon, Seonghwan Choi

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Achieving flexible fairness metrics in federated medical imaging by Huijun Xing, Rui Sun, Jinke Ren, Jun Wei, Chun-Mei Feng, Xuan Ding, Zilu Guo, Yu Wang, Yudong Hu, Wei Wei, Xiaohua Ban, Chuanlong Xie, Yu Tan, Xian Liu, Shuguang Cui, Xiaohui Duan, Zhen Li

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Advancements in image classification for environmental monitoring using AI by Jinjing Zhu, Ling Li

“…IntroductionAccurate environmental image classification is essential for ecological monitoring, climate analysis, disaster detection, and sustainable resource management. …”
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Functional network reorganization and memory impairment in unruptured brain arteriovenous malformations by Anqi Li, Xiaofeng Deng, Kexin Yuan, Yu Chen, Zhipeng Li, Xiaolin Chen, Yuanli Zhao

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Aberrant dynamic functional network connectivity in patients with diffuse axonal injury by Jian Li, Yao Wang, Yuanyuan Wang, Jie Zhan, Weiming Sun, Feng Ouyang, Xiumei Zheng, Lianjiang Lv, Zihe Xu, Jie Liu, Fuqing Zhou, Xianjun Zeng

“…This study aimed to examine the characteristics of static and dynamic functional network connectivity (FNC) in patients with DAI. Resting-state functional magnetic resonance imaging data were collected from 26 patients with DAI and 27 healthy controls. …”
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Developing an artificial intelligence-based progressive growing GAN for high-quality facial profile generation and evaluation through turing test and aesthetic analysis by Shahab Kavousinejad, Kazem Dalaie, Mohammad Behnaz, Soodeh Tahmasbi, Asghar Ebadifar, Hoori Mirmohammadsadeghi

“…Abstract This study aimed to develop a Progressive Growing Generative Adversarial Network with Gradient Penalty (WPGGAN-GP) to generate high-quality facial profile images, addressing the scarcity of diverse training data in orthodontics. …”
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AI-Powered Spectral Imaging for Virtual Pathology Staining by Adam Soker, Maya Almagor, Sabine Mai, Yuval Garini

“…Unstained human biopsy samples are scanned, and a Pix2Pix-based neural network generates realistic H&E-equivalent images. …”
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Automating field‐based floral surveys with machine learning by Nicholas Sookhan, Shane Sookhan, Devlin Grewal, J. Scott MacIvor

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YOLOv8 with Post-Processing for Small Object Detection Enhancement by Jinkyu Ryu, Dongkurl Kwak, Seungmin Choi

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Advancing Progressive Web Applications to Leverage Medical Imaging for Visualization of Digital Imaging and Communications in Medicine and Multiplanar Reconstruction: Software Deve... by Mohammed A. AboArab, Vassiliki T. Potsika, Alexis Theodorou, Sylvia Vagena, Miltiadis Gravanis, Fragiska Sigala, Dimitrios I. Fotiadis

“… BackgroundIn medical imaging, 3D visualization is vital for displaying volumetric organs, enhancing diagnosis and analysis. …”
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NEW EVALUATION METHOD FOR EFFICACY OF HYPOTENSIVE TREATMENT WITH ACE INHIBITORS by V. V. Shkarin, O. S. Belykh, E. V. Gurvich, E. A. Olkhovskaya, L. G. Yefremova, A. V. Tsiganova, U. Y. Ruzhentsova, N. T. Shilina, N. V. Sidorova

“…The method is based upon primary analysis of daily blood pressure monitoring data with subsequent transformation into a graphic form of BP values likelihood distribution over a plane. …”
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Multi-modal denoised data-driven milling chatter detection using an optimized hybrid neural network architecture by Haining Gao, Haoyu Wang, Hongdan Shen, Shule Xing, Yong Yang, Yinlin Wang, Wenfu Liu, Lei Yu, Mazhar Ali, Imran Ali Khan

“…To address the low accuracy in chatter detection caused by the limitations of both one-dimensional temporal and two-dimensional image modal information, this study proposes a multi-modal denoised data-driven milling chatter detection method using an optimized hybrid neural network architecture. …”
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Image recoloring detection based on inter-channel correlation by Nuo CHEN, Shuren QI, Yushu ZHANG, Mingfu XUE, Zhongyun HUA

“…Image recoloring is an emerging editing technique that can change the color style of an image by modifying pixel values.With the rapid proliferation of social networks and image editing techniques, recolored images have seriously hampered the authenticity of the communicated information.However, there are few works specifically designed for image recoloring.Existing recoloring detection methods still have much improvement space in conventional recoloring scenarios and are ineffective in dealing with hand-crafted recolored images.For this purpose, a recolored image detection method based on inter-channel correlation was proposed for conventional recoloring and hand-crafted recoloring scenarios.Based on the phenomenon that there were significant disparities between camera imaging and recolored image generation methods, the hypothesis that recoloring operations might destroy the inter-channel correlation of natural images was proposed.The numerical analysis demonstrated that the inter-channel correlation disparities can be used as an important discriminative metric to distinguish between recolored images and natural images.Based on such new prior knowledge, the proposed method obtained the inter-channel correlation feature set of the image.The feature set was extracted from the channel co-occurrence matrix of the first-order differential residuals of the differential image.In addition, three detection scenarios were assumed based on practical situations, including scenarios with matching and mismatching between training-testing data, and scenario with hand-crafted recoloring.Experimental results show that the proposed method can accurately identify recolored images and outperforms existing methods in all three hypothetical scenarios, achieving state-of-the-art detection accuracy.In addition, the proposed method is less dependent on the amount of training data and can achieve fairly accurate prediction results with limited training data.…”
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The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists by Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Silva, Erika Dunning, Gerd Gühne, Marc Huten, Michiharu Hyogo, Davide Iannone, Sam Lee, Christian Magliano, Manya Sharma, Allan Tarr, John Yablonsky, Sovan Acharya, Fred Adams, Thomas Barclay, Benjamin T. Montet, Susan Mullally, Greg Olmschenk, Andrej Prša, Elisa Quintana, Robert Wilson, Hasret Balcioglu, Ethan Kruse, The Eclipsing Binary Patrol Collaboration

“…We combed Sectors 1–82 of the TESS full-frame image data searching for eclipsing binary stars using a neural network that identified ∼1.2 million stars with eclipse-like features. …”
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A unified multimodal learning method for urban functional zone identification by fusing inner-street visual–textual information from street-view and satellite images by Jiajun Chen, Runyu Fan, Hongyang Niu, Zijian Xu, Jining Yan, Weijing Song, Ruyi Feng

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Development and evaluation of machine learning models for premixed flame classification in different hydrogen-natural gas proportions using images and audio by Pedro Narvaez, Alejandro Lopez, Jousef E. Karam, Alejandro Restrepo, Andrés A. Amell

“…A comprehensive analysis was conducted using audio signals, which were converted into Mel spectrograms, alongside image data. …”
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Enhancing Diabetic Foot Ulcer Classification Through Fine-Tuned Multilevel CNN by Elineide Silva Dos Santos, Rodrigo de Melo Souza Veras, Francisco Das Chagas Torres Dos Santos, Marcia Ito, Andrea Gomes Campos Bianchi, Kelson Romulo Teixeira Aires, Joao Manuel R. S. Tavares

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