Modeling and Data Analysis of Bistatic Bottom Reverberation from a Towed Horizontal Array by Zhaohua Su, Jie Zhuo, Chao Sun

“…Moreover, the regional segmentation method simulates reverberations across various receiving beams, ignoring scatterers in other areas. …”
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U-Net-Based Fingerprint Enhancement for 3D Fingerprint Recognition by Mohammad Mogharen Askarin, Min Wang, Xuefei Yin, Xiuping Jia, Jiankun Hu

“…In this work, we propose an image segmentation approach using the deep learning U-Net to enhance the fingerprint contrast. …”
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Artificial Intelligence for the Prenatal Ultrasound Diagnosis of Congenital Heart Disease: A Narrative Review by Arianna Riva, Mariachiara Guerra, Stefania Di Gangi, Paola Veronese, Vladimiro L Vida

“…However, nowadays, its integration into routine clinical practice gives rise to several issues.…”
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Enhanced remote sensing image feature classification using STFF-PSPNet by Haiying Li, Jiaqi Gao, Yang Liu, Chenxi Huang, Lijun Li, Liqiang Zhang

“…Abstract Semantic segmentation of remotely sensed images is crucial for urban planning and change detection, yet faces issues like sample imbalance and low data quality. …”
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Research on Walnut (<i>Juglans regia</i> L.) Yield Prediction Based on a Walnut Orchard Point Cloud Model by Heng Chen, Jiale Cao, Jianshuo An, Yangjing Xu, Xiaopeng Bai, Daochun Xu, Wenbin Li

“…This study aims to develop a method for predicting walnut (<i>Juglans regia</i> L.) yield based on the walnut orchard point cloud model, addressing issues such as low efficiency, insufficient accuracy, and high costs in traditional methods. …”
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Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review by Jia-Mei Chen, Yan Li, Jun Xu, Lei Gong, Lin-Wei Wang, Wen-Lou Liu, Juan Liu

“…Moreover, we discussed the issues of current analysis, and some directions for future research.…”
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Automating hock wound detection in dairy cattle by W. Flanders, P.S. Basran, M. Wieland

“…Accurate hock scoring is vital because it can indicate issues such as poor bedding quality or inadequate space, which directly affect the health and productivity of the herd. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…But OCR technology is plagued with persistent issues, such as environmental factors (poor lighting, bad weather effects, container shape…), text recognition challenges (skewed text, motion blur, segmentation failure), and hardware reliability concerns (camera malfunction, network instability, and delays in real-time processing). …”
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Voxel-Based Navigation: A Systematic Review of Techniques, Applications, and Challenges by Lei Niu, Zhiyong Wang, Zhaoyu Lin, Yueying Zhang, Yingwei Yan, Ziqi He

“…Additionally, various issues related to voxel-based navigation are addressed. …”
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Enhancing named entity recognition with a novel BERT‐BiLSTM‐CRF‐RC joint training model for biomedical materials database by Mufei Li, Yan Zhuang, Ke Chen, Lin Han, Xiangfeng Li, Yongtao wei, Xiangdong Zhu, Mingli Yang, Guangfu Yin, Jiangli Lin, Xingdong Zhang

“…Additionally, segmentation issues are further mitigated through a segmented combined voting‐ and positive‐sample‐coverage technique. …”
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A Review on MR Image Intensity Inhomogeneity Correction by Zujun Hou

“…They are often formulated together with image segmentation within one framework and the overall performance is highly dependent on the segmentation process. …”
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A fully-automated technique for cartilage morphometry in knees with severe radiographic osteoarthritis – Method development and validation by Wolfgang Wirth, Felix Eckstein

“…Sensitivity to change was greatest for manual segmentation of DESS (SRM ​≥ ​−0.69; automated: ≥−0.56) and for automated segmentation of FLASH (≥−0.74; manual ≥−0.44). …”
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Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

“…Despite significant progress in semantic segmentation achieved by convolutional neural networks (CNNs), the local sensory field of CNNs poses difficulties in differentiating between landslides and bare surfaces. …”
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A text-speech multimodal Chinese named entity recognition model for crop diseases and pests by Ruilin Liu, Xuchao Guo, HongMei Zhu, Lu Wang

“…However, existing NER-CDP methods rely heavily on plain text or external features such as radicals and font types and have limited effect on improving word segmentation. In this paper, we propose a multimodal named entity recognition model (CDP-MCNER) based on cross-modal attention to solve the issue of the performance degradation of the NER model caused by potential word segmentation errors. …”
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Large Scale Land Cover Mapping in Ontario, Canada, Using a Deep Learning Framework by Fariba Mohammadimanesh

“…As the only deep learning model, examined in this study, combining convolutional and transformer blocks, MobileUNetR demonstrates the superiority of hybrid architectures for large-scale semantic segmentation. This is due to its capability in capturing both local and global features, which are essential for semantic segmentation of heterogeneous land cover classes with varying sizes and spectral signatures.…”
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MATE-ViT: A multi-channel contrast-limited adaptive time-frequency enhancement and vision transformer framework for bearing fault diagnosis by Jiangdong Zhao, Jiao Yu, Wenming Wang, Ji Huang, Xiaolu Ma

“…To address the issues of low contrast, unclear local details, and the difficulty of existing deep learning models in capturing long-range dependencies in time-frequency images generated by current time-frequency construction methods, this paper proposes a bearing fault diagnosis framework (MATE-ViT) based on multi-channel contrast-limited adaptive time-frequency enhancement (CLAHE) and vision transformer (ViT). …”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…In perspective, the advancements may include increasing the size of the annotated data-set and fine-tuning the model due to detection issues of non-solitary nodules.…”
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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

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Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration by Tsabeeh Salah M. Mahmoud, Adnan Munawar, Muhammad Zeeshan Nawaz, Yuanyuan Chen

“…This study explored the groundwork for precise multispectral transmission image segmentation and classification.…”
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Global research landscape on artificial intelligence in echocardiography from 1997 to 2024: Bibliometric analysis by Leichong Chen, Wenwen Chen, Ye Zhu, Zisang Zhang, Tingting Liu, Li Zhang

“…Based on keyword analysis, the current research hotspots were mainly focused on image segmentation, heart failure, deep learning, and pulmonary hypertension. …”
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