RSPS-SAM: A Remote Sensing Image Panoptic Segmentation Method Based on SAM by Zhuoran Liu, Zizhen Li, Ying Liang, Claudio Persello, Bo Sun, Guangjun He, Lei Ma

“…To mitigate this issue, this paper leverages the advantages of the Segment Anything Model (SAM), which can segment any object in remote sensing images without requiring any annotations and proposes a high-resolution remote sensing image panoptic segmentation method called Remote Sensing Panoptic Segmentation SAM (RSPS-SAM). …”
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Human Brain-Inspired Network Using Transformer and Feedback Processing for Cell Image Segmentation by Hinako Mitsuoka, Kazuhiro Hotta

“…Semantic segmentation of microscopy cell images by deep learning plays a crucial role in advancing medicine and cell biology research. …”
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Semantic segmentation of optical satellite images for the illegal construction detection using transfer learning by Yashasvi Mehta, Abdullah Baz, Shobhit K. Patel

“…Illegal construction poses significant challenges to economic development and social harmony. To tackle this issue, there is an urgent need for an automated illegal building monitoring system that can accurately identify and notify authorities about unlawful constructions. …”
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Laboratory Evaluation of the Platelet Component of Hemostasis in acute Coronary Syndrome With ST Segment Elevation by D. Markhulia, K. A. Popugaev, D. A. Sychev, M. V. Vatsik-Gorodetskaya, G. A. Gazaryan, M. A. Godkov, A. A. Kachanova, K. V. Kiselev, E. V. Klychnikova, D. A. Kosolapov, I. M. Kuzmina, K. B. Mirzaev, O. K. Popugaeva, S. N. Tuchkova

“…The study of antiplatelet therapy and resistance to it is a pressing issue in modern cardiology. This is important not only for determining the effectiveness of treatment for each patient, but also for personalizing therapy based on genetic characteristics. …”
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“In the hour of trial”: the spiritual life and socio-political issues in sermons Archimandrite Alexander (Lovchiy) by Murzin Evgenii

“…The article is devoted to the study of the Orthodox segment of the religious and social thought in Germany during the Third Reich. …”
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Intracranial hemorrhage segmentation and classification framework in computer tomography images using deep learning techniques by S. Nafees Ahmed, P. Prakasam

“…There is potential for this suggested approach to be expanded in the future to handle further medical picture segmentation issues. Intraventricular hemorrhage (IVH), Epidural hemorrhage (EDH), Intraparenchymal hemorrhage (IPH), Subdural hemorrhage (SDH), Subarachnoid hemorrhage (SAH) are the subtypes involved in intracranial hemorrhage (ICH) whose DICE coefficients are 0.77, 0.84, 0.64, 0.80, and 0.92 respectively.The proposed method has great deal of clinical application potential for computer-aided diagnostics, which can be expanded in the future to handle further medical picture segmentation and to tackle with the involved issues.…”
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The role of matrix metalloproteinases in left ventricular remodeling in patients with ST-segment elevation myocardial infarction by T. B. Pecherina, O. V. Gruzdeva, O. L. Barbarash

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A Medical Image Semantics Segmentation Method Based on Image Pre-processing and Image Transformer by Li Zhaopeng

“…Semantics segmentation is a task aiming at classifying each pixel of an image into a category. …”
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MICROSURGERY OF ANEURYSM WITHIN THE FOURTH SEGMENT OF LEFT VERTEBRAL ARTERY AND POSTERIOR INFERIOR CEREBELLAR ARTERY by AMIN R. Shabaev, ANTON N. Kazantsev, ANDREY V. Dubovoy, ROMAN S. Tarasov, ANDREY V. Mironov, ELENA V. Ruban

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Optimal Anisotropic Guided Filtering in retinal fundus imaging: A dual approach to enhancement and segmentation. by G Tirumala Vasu, Samreen Fiza, Subba Rao Polamuri, K Reddy Madhavi, Thejaswini R, Venkataramana Guntreddi

“…Many traditional methods of segmentation and enhancement encounter issues with visual distortion, ghost artifacts, spatially inconsistent structures, and edge information preservation as a result of the diffusion of spatial intensities at the edges. …”
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Bias-Aware Generative AI for fair customer segmentation: a VAE and BIRCH clustering approach by Shivranjani Bharatbhai Gajjar, Vivekanand Mishra

“…We attempt to solve these issues with a Bias-Aware Generative AI (BiA-GAI) framework, using the Mall Customer Segmentation dataset. …”
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Parameter-efficient weakly supervised referring video object segmentation via chain-of-thought reasoning by Xing Wang, Zhe Xu, Yuanshi Zheng, Handing Wang

“…In this paper, we propose a novel parameter-efficient framework under weak supervision, dubbed ReferringAdapter, to ameliorate both of issues. Specifically, we propose to adapt an off-the-shelf image segmentation model for RVOS by plugging a small set of trained parameters, i.e., an adapter, into the intermediate layer. …”
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MTMU: Multi-domain Transformation based Mamba-UNet designed for unruptured intracranial aneurysm segmentation by Bing Li, Nian Liu, Jianbin Bai, Jianfeng Xu, Yi Tang, Yan Liu

“…To relieve these issues, this article proposes a multi-domain transformation-based Mamba-UNet (MTMU) for UIA segmentation. …”
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CMSAF-Net: integrative network design with enhanced decoder for precision segmentation of pear leaf diseases by Jie Ding, Wenwen Xu, Xin Shu, Wenyu Wang, Shuxia Chen, Yunzhi Wu

“…To address these issues, this study proposes a novel segmentation model, CMSAF-Net, for pear leaf diseases. …”
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LSL-SS-Net: level set loss-guided semantic segmentation networks for landslide extraction by Yueheng Yang, Zelang Miao, Xiaojing Li, Hua Zhang, Shuai Chen

“…This study presents a level set loss-guided semantic segmentation network, which can be integrated with different semantic segmentation networks, to address these issues. …”
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FFAE-UNet: An Efficient Pear Leaf Disease Segmentation Network Based on U-Shaped Architecture by Wenyu Wang, Jie Ding, Xin Shu, Wenwen Xu, Yunzhi Wu

“…The accurate pest control of pear tree diseases is an urgent need for the realization of smart agriculture, with one of the key challenges being the precise segmentation of pear leaf diseases. However, existing methods show poor segmentation performance due to issues such as the small size of certain pear leaf disease areas, blurred edge details, and background noise interference. …”
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Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture by Guang Yang, Junyi Yang, Wenyao Fan, Donghe Yang

“…Underwater fish image segmentation is a crucial technique in marine fish monitoring. …”
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YOLOv8-TEA: Recognition Method of Tender Shoots of Tea Based on Instance Segmentation Algorithm by Wenbo Wang, Yidan Xi, Jinan Gu, Qiuyue Yang, Zhiyao Pan, Xinzhou Zhang, Gongyue Xu, Man Zhou

“…However, due to the diverse growth postures of tender shoots and complex growth environments in tea plants, traditional tea picking machines are unable to precisely select the tender shoots, and the picking of high-end and premium tea still relies on manual labor, resulting in low efficiency and high costs. To address these issues, an instance segmentation algorithm named YOLOv8-TEA is proposed. …”
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ACNet: An Attention–Convolution Collaborative Semantic Segmentation Network on Sensor-Derived Datasets for Autonomous Driving by Qiliang Zhang, Kaiwen Hua, Zi Zhang, Yiwei Zhao, Pengpeng Chen

“…Although deep learning methods have made significant progress, two main challenges remain: first, the difficulty in balancing global and local features leads to blurred object boundaries and misclassification; second, conventional convolutions have limited ability to perceive irregular objects, causing information loss and affecting segmentation accuracy. To address these issues, this paper proposes a global–local collaborative attention module and a spider web convolution module. …”
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Comparative Analysis of Multi-Resolution Remote Sensing Data for Accurate Road Segmentation in Urban Environments by M. R. Çevikalp, B. Mutlu, M. Yanalak, N. Musaoğlu

“…Deep learning models like U-Net have enhanced road segmentation by accurately capturing complex features. …”
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