MGFNet: An MLP-dominated gated fusion network for semantic segmentation of high-resolution multi-modal remote sensing images by Kan Wei, JinKun Dai, Danfeng Hong, Yuanxin Ye

“…The heterogeneity and complexity of multimodal data in high-resolution remote sensing images significantly challenges existing cross-modal networks in fusing the complementary information of high-resolution optical and synthetic aperture radar (SAR) images for precise semantic segmentation. To address this issue, this paper proposes a multi-layer perceptron (MLP) dominated gate fusion network (MGFNet). …”
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A Semisupervised Classification Method for Riverbed Benthic Sediments Using Integrated Superpixel Segmentation and Confident Learning Sample Enhancement by Yaxue Wang, Yuewen Sun, Xiaodong Cui, Tianyu Yun, Xianhai Bu, Fanlin Yang

“…However, limitations in underwater field sampling techniques result in insufficient sampling data, leaving many unlabeled high-resolution acoustic data underutilized, which hinders practical training and deployment of classifiers. To address this issue, this article proposes a sediment sample enhancement method based on superpixel segmentation, confident learning (CL), and active learning (AL) to improve model performance. …”
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Automated Cervical Cancer Screening Using Single-Cell Segmentation and Deep Learning: Enhanced Performance with Liquid-Based Cytology by Mariangel Rodríguez, Claudio Córdova, Isabel Benjumeda, Sebastián San Martín

“…Cervical cancer (CC) remains a significant health issue, especially in low- and middle-income countries (LMICs). …”
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MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation by Ruiyuan Chen, Saiqi He, Junjie Xie, Tao Wang, Yingying Xu, Jiangxiong Fang, Xiaoming Zhao, Shiqing Zhang, Guoyu Wang, Hongsheng Lu, Zhaohui Yang

“…Although several impressive deep learning architectures based on convolutional neural networks (CNNs) and Transformers have recently demonstrated remarkable performance, there is still potential for further performance improvement due to their inherent limitations in capturing feature correlations of input data. To address this issue, this paper proposes a novel encoder-decoder architecture called MedFuseNet that aims to fuse local and global deep feature representations with hybrid attention mechanisms for medical image segmentation. …”
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Wavelet Guided Visual State Space Model and Patch Resampling Enhanced U-Shaped Structure for Skin Lesion Segmentation by Shuwan Feng, Xiaowei Chen, Shengzhi Li

“…On the other hand, RSIF tackles the issue of information loss that often occurs during the upsampling process, which can result in blurred or missing fine-grained details critical for accurate segmentation. …”
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Preoperative Spino Cranial Angle Predicts Adjacent Segment Degeneration After Single-Level Anterior Cervical Discectomy and Fusion by Li Y, Cheng P, Zhang X, Cheng C

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Relationship Between Glycosylated Hemoglobin Concentration and Prognosis of Acute ST-Segment Elevation Myocardial Infarction in Non-Diabetic Patients by Liu Z, Gao J, Hu W, Yan P, Lu J, Lei T, Xia J

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More than 1,001 problems with protein domain databases: transmembrane regions, signal peptides and the issue of sequence homology. by Wing-Cheong Wong, Sebastian Maurer-Stroh, Frank Eisenhaber

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Performance of Commercial Deep Learning-Based Auto-Segmentation Software for Prostate Cancer Radiation Therapy Planning: A Systematic Review by Curtise K. C. Ng

“…As yet, there is no systematic review focusing on benefits and issues of commercial deep learning-based auto-segmentation (DLAS) software for prostate cancer (PCa) radiation therapy (RT) planning despite that NRG Oncology has underscored such necessity. …”
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MFSE-TransUNet: A Thyroid Nodule Ultrasound Image Segmentation Network Integrated With Dynamic Feature Calibration and Edge Enhancement by Ye Lu, Jiaojiao Jing, Wenbo Zhang, Yali Kong

“…Thus, accurate pixel-level segmentation is of great value for quantifying nodule morphology, tracking lesion progression, and planning surgery. …”
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IMPLEMENTATION OF SEGMENTATION AND ARCHITECTONICS PRINCIPLES IN THE TEXTS OF JUDICIAL DECISIONS (BASED ON JUDICIAL DECISIONS OF SUPREME COURTS OF THE ANGLO-SAXON LEGAL SYSTEM) by O. Suetina

“…The relevance of the study of texts of court decisions in the modern world is due to both the social demand for the development of legal linguistic issues, and the need to accumulate, observe and generalize the research material of legal texts. …”
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MFAFNet: Multi-Scale Feature Adaptive Fusion Network Based on DeepLab V3+ for Cloud and Cloud Shadow Segmentation by Yijia Feng, Zhiyong Fan, Ying Yan, Zhengdong Jiang, Shuai Zhang

“…However, existing segmentation models often suffer from issues such as losing fine details, blurred boundaries, and false positives or negatives. …”
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A novel hybrid deep learning approach combining deep feature attention and statistical validation for enhanced thyroid ultrasound segmentation by Tathagat Banerjee, Davinder Paul Singh, Debabrata Swain, Shubham Mahajan, Seifedine Kadry, Jungeun Kim

“…Abstract An effective diagnosis system and suitable treatment planning require the precise segmentation of thyroid nodules in ultrasound imaging. …”
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RDCU-Net: A Multi-Scale Residual Dilated Convolution U-Net with Spatial Pyramid Pooling for Brain Tumor Segmentation by Mohammad Soltani-Gol, Akbar Asgharzadeh-Bonab, Hamid Soltanian-Zadeh, Jalil Mazlum

“…Deep learning methods are effective for medical image segmentation, but they struggle with tumors in magnetic resonance images (MRI) due to variations in intensity and appearance. …”
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SE-TransUNet-Based Semantic Segmentation for Water Leakage Detection in Tunnel Secondary Linings Amid Complex Visual Backgrounds by Renjie Song, Yimin Wu, Li Wan, Shuai Shao, Haiping Wu

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GWSC-SegMamba: Gate Wavelet Spatial Convolution Enhanced State Space Model for Multi-Temporal Agricultural Land Segmentation by Yohanes Fridolin Hestrio, Aprinaldi Jasa Mantau, Wisnu Jatmiko

“…We present GWSC-SegMamba, an innovative hybrid architecture that integrates State Space Models (SSMs) with Gate Wavelet Convolution (GWC) and Gate Spatial Convolution (GSC) components to tackle multi-temporal agricultural segmentation issues. The GWC component conducts multi-resolution analysis with discrete wavelet transforms to address spatial resolution constraints for medium-resolution satellite data, whereas the GSC component identifies spatial correlations essential for delineating crop boundaries. …”
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A Two-Stage Deep Learning Method for Marine Oil Spill Localization and Segmentation From Synthetic Aperture Radar Images by Xudong Huang, Biao Zhang, William Perrie

“…Existing methods for detecting oil spills using synthetic aperture radar (SAR) often face challenges related to algorithm complexity, limited data availability, and practical implementation. To address these issues, we propose a two-stage deep learning (DL) method to automatically localize and segment oil spills in Sentinel-1 SAR images. …”
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RDAU-Net: A U-Shaped Semantic Segmentation Network for Buildings near Rivers and Lakes Based on a Fusion Approach by Yipeng Wang, Dongmei Wang, Teng Xu, Yifan Shi, Wenguang Liang, Yihong Wang, George P. Petropoulos, Yansong Bao

“…To address the above issues, the present study proposes the design of a U-shaped segmentation network of buildings called RDAU-Net that works through extraction and fuses a convolutional neural network and a transformer to segment buildings. …”
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MFFTNet: A Novel 3D Point Cloud Segmentation Network Based on Multi-Scale Feature Fusion and Transformer Architecture by Hao Bai, Xiongwei Li, Qing Meng, Shulong Zhuo, Lili Yan

“…To address these issues, this paper proposes a novel Point Cloud Segmentation Network based on multi-scale feature fusion and Transformer architecture (MFFTNet). …”
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Loosening rocks detection at Draa Sfar deep underground mine in Morocco using infrared thermal imaging and image segmentation models by Kaoutar Clero, Said Ed-Diny, Mohammed Achalhi, Mouhamed Cherkaoui, Imad El Harraki, Sanaa El Fkihi, Intissar Benzakour, Tarik Soror, Said Rziki, Hamd Ait Abdelali, Hicham Tagemouati, François Bourzeix

“…The findings confirm that thermal image segmentation can serve as an alternative method for predicting rockfalls and monitoring geotechnical issues in underground mines. …”
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