Preliminary application of a cervical vertebra segmentation method based on Transformer and diffusion model for lateral cephalometric radiographs in orthodontic clinical practice by LIU Yang, WU Mengyi, HU Yao, QI Kun, WANG Yubin, ZHAO Yue, SONG Jinlin

“…Objective·To construct a cervical vertebra image segmentation model by using a diffusion model with the Transformer deep learning algorithm, and evaluate its segmentation performance, to address the clinical challenge of accurately assessing complex changes in skeletal morphology during the growth and developmental peaks of malocclusion.Methods·Accurate cervical vertebra segmentation was performed on cephalometric radiographs from 185 orthodontic patients (44 cases from the Stomatological Hospital of Chongqing Medical University and 141 cases from the Stomatological Hospital of Xi'an Jiaotong University) by using a method combining Transformer and diffusion models. …”
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Aerial image segmentation of embankment dams based on multispectral remote sensing: a case study in the Belo Monte Hydroelectric Complex, Pará, Brazil by Carlos André de Mattos Teixeira, Thabatta Moreira Alves de Araujo, Evelin Cardoso, Marcos Antonio Costantin Filho, João Weyl Costa, Carlos Renato Lisboa Frances

“…The main objectives of this study are to assess the classification performance of the algorithm in segmenting earth-rock dams and the contribution of non-visible band reflectance data to the overall model performance. …”
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A Monocular Vision-Based Safety Monitoring Framework for Offshore Infrastructures Utilizing Grounded SAM by Sijie Xia, Rufu Qin, Yang Lu, Lianjiang Ma, Zhenghu Liu

“…By combining advanced computer vision techniques such as Grounded SAM and horizon-based self-calibration, the proposed framework achieves accurate vessel detection, instance segmentation, and distance estimation. The model integrates open-vocabulary object detection and zero-shot segmentation, achieving high performance without additional training. …”
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Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnex... by Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu

“…Abstract Objective To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS). …”
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Real-Time Pipeline Fault Detection in Water Distribution Networks Using You Only Look Once v8 by Goodnews Michael, Essa Q. Shahra, Shadi Basurra, Wenyan Wu, Waheb A. Jabbar

“…The YOLOv8 model is employed for object detection due to its exceptional performance in detecting objects, segmentation, pose estimation, tracking, and classification. …”
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BiFormer for Scene Graph Generation Based on VisionNet With Taylor Hiking Optimization Algorithm by S. Monesh, N. C. Senthilkumar

“…In the SGG, visually grouped graphs are generated by considering edges as visual relationships between objects and nodes as object classes. …”
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Research on Recognition of Green Sichuan Pepper Clusters and Cutting-Point Localization in Complex Environments by Qi Niu, Wenjun Ma, Rongxiang Diao, Wei Yu, Chunlei Wang, Hui Li, Lihong Wang, Chengsong Li, Pei Wang

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Delimitation of Landslide Areas in Optical Remote Sensing Images Across Regions via Deep Transfer Learning by Zan Wang, Shengwen Qi, Yu Han, Bowen Zheng, Yu Zou, Yue Yang

“…A workflow for transferring deep learning models pretrained on other regions for landslide area delimitation on new regions with a relatively small number of annotated training samples is developed. A post-processing module is integrated into the Mask R-CNN architecture to address the challenge of overlapping mask predictions for individual landslide objects. …”
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Occlusion Vehicle Target Recognition Method Based on Component Model by Haorui Han, Hanshan Li

“…Based on the U-net codec structure, combining multi-scale detection and double constraints loss to improve the visual region segmentation under complex background (VSRS) performance. …”
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Two‐stage video anomaly detection based on dual‐stream networks and multi‐instance learning by Dejun Zhang, Wenbo Fang, Yuhang Liu, Zirong Lyu, Chen Xiong, Zhan Wang

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Toward unsupervised building extraction from very high-resolution remote sensing images using SAM and CLIP by Chenxiao Zhang, Peng Yue

“…First, we introduce a zero-shot pseudo-label generation method, guided by the integration of the Segment Anything Model (SAM) and the CLIP model. To address the misclassification of fragmented objects, we design a zoom-out strategy to restore broken segments. …”
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End-to-End Horse Gait Classification in Uncontrolled Environments Using Inertial Sensors by Mahaut Gerard, Sandrine Hanne-Poujade, Guillaume Dubois, Henry Chateau, Neila Mezghani

“…Veterinarians typically investigate horses’ lameness through visual examination at separate gaits (walk, trot, gallop). …”
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Automatic collateral quantification in acute ischemic stroke using U2-net by Qingqing Lu, Qingqing Lu, Hongyi Chen, Junyan Fu, Xiaodong Zheng, Yiren Xu, Yuning Pan

“…ObjectivesTo harness the U2-Net deep learning framework for automated quantification of collateral circulation in acute ischemic stroke (AIS) via computed tomography angiography (CTA) images, comparing its performance against traditional visual collateral scores (vCS).MethodsA cohort of 118 confirmed AIS cases was assembled and stratified into 94 development and 24 test cases. …”
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Comparison of Hybrid Dynamic Stabilization with TLIF Versus Dynamic Stabilization Alone in Degenerative Lumbar Instability by Uzay Erdogan, Gurkan Berikol, Ibrahim Taha Albas, Mehmet Yigit Akgun, Tunc Oktenoglu, Ozkan Ates, Ali Fahir Ozer

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A Hybrid Algorithm for Contour Thinning in Image Processing by Mamatov Narzullo, Niyozmatova Nilufar, Jalelova Malika, Samijonov Abdurashid, Samijonov Boymirzo

“…Visual data processing is a rapidly expanding field, with image processing aimed at enhancing image features for object recognition. …”
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I-MPN: inductive message passing network for efficient human-in-the-loop annotation of mobile eye tracking data by Hoang H. Le, Duy M. H. Nguyen, Omair Shahzad Bhatti, László Kopácsi, Thinh P. Ngo, Binh T. Nguyen, Michael Barz, Daniel Sonntag

“…Furthermore, we demonstrate exceptional efficiency in data annotation processes and surpass prior interactive methods that use complete object detectors, combine detectors with convolutional networks, or employ interactive video segmentation.…”
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Big2Small: Learning from masked image modelling with heterogeneous self‐supervised knowledge distillation by Ziming Wang, Shumin Han, Xiaodi Wang, Jing Hao, Xianbin Cao, Baochang Zhang

“…Extensive experiments show that it adapts well to various models and sizes, consistently achieving state‐of‐the‐art performance in image classification, object detection, and semantic segmentation tasks. …”
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OCT5k: A dataset of multi-disease and multi-graded annotations for retinal layers by Mustafa Arikan, James Willoughby, Sevim Ongun, Ferenc Sallo, Andrea Montesel, Hend Ahmed, Ahmed Hagag, Marius Book, Henrik Faatz, Maria Vittoria Cicinelli, Amani A. Fawzi, Dominika Podkowinski, Marketa Cilkova, Diana Morais De Almeida, Moussa Zouache, Ganesham Ramsamy, Watjana Lilaonitkul, Adam M. Dubis

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Unraveling Cyberbullying Dynamis: A Computational Framework Empowered by Artificial Intelligence by Liliana Ibeth Barbosa-Santillán, Bertha Patricia Guzman-Velazquez, Ma. Teresa Orozco-Aguilera, Leticia Flores-Pulido

“…Segmentation issues and the presence of background objects or people further compound this complexity. …”
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Glaucoma detection from retinal fundus images using graph convolution based multi-task model by Satyabrata Lenka, Zefree Lazarus Mayaluri, Ganapati Panda

“…The intended objective of the present study is to come up with and train a distinctive multi-task deep learning model for automated fundus image segmentation and classification. …”
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