Instance segmentation and automated pig posture recognition for smart health management by Md Nasim Reza, Md Sazzadul Kabir, Md Asrakul Haque, Hongbin Jin, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…However, a potential solution is computer vision-based monitoring of posture and movement. The objective of this study was to recognize and detect pig posture using a masked-based instance segmentation for automated pig monitoring in a closed pig farm environment. …”
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Large multimodal model for open vocabulary semantic segmentation of remote sensing images by Bing Liu, Xiaohui Chen, Anzhu Yu, Fan Feng, Jiaying Yue, Xuchu Yu

“…Conventional remote sensing image semantic segmentation tasks require training specialized models for specific categories of ground objects, which often fail to recognize unseen ground object categories during the training process. …”
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Visual Automatic Localization Method Based on Multi-level Video Transformer by Qiping ZOU, Botao LI, Saian CHEN, Xi GUO, Taohong ZHANG

“…From this sequence, the clearest image is meticulously selected, and its index is recorded as the actual value label, serving as a critical dataset for training and testing the proposed model.　This comprehensive approach ensures the precision of frame selection and significantly contributes to the reliability and efficiency of automated processes that rely on precise visual data for operational accuracy.Results and Disccussions The empirical assessment of the Multi-level Video Transformer model demonstrated encouraging outcomes across its three variants, achieving classification accuracies of 87.2%, 88.6%, and 88.9% on a custom video dataset. …”
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Visual Prompt Learning of Foundation Models for Post-Disaster Damage Evaluation by Fei Zhao, Chengcui Zhang, Runlin Zhang, Tianyang Wang

“…In response to the urgent need for rapid and precise post-disaster damage evaluation, this study introduces the Visual Prompt Damage Evaluation (ViPDE) framework, a novel contrastive learning-based approach that leverages the embedded knowledge within the Segment Anything Model (SAM) and pairs of remote sensing images to enhance building damage assessment. …”
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SAMSurg: Surgical Instrument Segmentation in Robotic Surgeries Using Vision Foundation Model by Nevin M. Matasyoh, Franziska Mathis-Ullrich, Ramy A. Zeineldin

“…To address these limitations in robotic surgeries, we introduce SAMSurg, an adaptation of the Segment Anything Model (SAM). This vision foundation model accurately segments diverse objects in images for various computer vision applications. …”
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Hard Example Mining Method for Visual Perception Based on Multi-sensor Fusion by Jun LIN, Wenbo PAN, Jun YOU, Yanghan XU

“…Hard examples for visual perception can improve the performance of object detection effectively in autonomous driving scenes. …”
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Visual language transformer framework for multimodal dance performance evaluation and progression monitoring by Lei Chen

“…Our model evaluates three key tasks: (i) multilabel dance classification, (ii) dance quality estimation, and (iii) dance-music synchronization, leveraging primitive-based segmentation and multi-modal inputs. During the pre-training phase, we utilize contrastive loss to capture primitive-based features from complex dance motion and music data. …”
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Model-Based Segmentation-Supported Camera Tracking in Fab’s Indoor Environments by Jeonghyeon Ahn, Jungho Ha, Jaemin Son, Junghyun Han

“…The estimation accuracy is significantly increased by adopting an instance segmentation network. It is trained with a dataset, which is extracted from the target indoor environment and processed by our own data engine. …”
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Part-Based Visual Tracking via Online Weighted P-N Learning by Heng Fan, Jinhai Xiang, Jun Xu, Honghong Liao

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Development of an Algorithm for Semantic Segmentation of Earth Remote Sensing Data to Determine Phytoplankton Populations by Yu. V. Belova, I. F. Razveeva, E. O. Rakhimbaeva

“…Graphical visualization of the results of CNN learning on the training and validation sets showed good quality of model learning. …”
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Research on Tongue Image Segmentation and Classification Methods Based on Deep Learning and Machine Learning by Bin Liu, Zeya Wang, Kang Yu, Yunfeng Wang, Haiying Zhang, Tingting Song, Hao Yang

“…The proposed approach enables accurate and efficient tongue image segmentation, provides an intuitive visualization of tongue color distribution, and objectively analyzes and quantifies the proportion of different tongue color categories. …”
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Weakly-Supervised Segmentation-Based Quantitative Characterization of Pulmonary Cavity Lesions in CT Scans by Wenyu Xing, Yanping Yang, Yanan Zhou, Tao Jiang, Yifang Li, Yuanlin Song, Dongni Hou, Dean Ta

“…Next, the visualized lesion was generated from the activation region of the classification network using gradient-weighted class activation mapping, and image processing was applied for post-processing to obtain the expected segmentation results of cavity lesions. …”
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PXseg: automatic tooth segmentation, numbering and abnormal morphology detection based on CBCT and panoramic radiographs by Raokaijuan Wang, Fangyuan Cheng, Guangsheng Dai, Jiayu Zhang, Chengmin Fan, Jinghong Yu, Juan Li, Fulin Jiang

“…Abstract Objective PXseg, a novel approach for tooth segmentation, numbering and abnormal morphology detection in panoramic X-ray (PX), was designed and promoted through optimizing annotation and applying pre-training. …”
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Modeling and construction of nomogram of cage subsidence after single-segment transforaminal lumbar interbody fusions by Jinxiang Zhan, Qipeng Wei, Weijun Guo, Zihao Liu, Shiji Chen, Qingyan Huang, Dongling Cai

“…Abstract Objective The purpose of this study is to explore and analyze the risk factors for interbody cage subsidence in patients undergoing single-segment transforaminal lumbar interbody fusion (TLIF) and to construct and validate a visual nomogram risk prediction model. …”
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Dual-stage segmentation and classification framework for skin lesion analysis using deep neural network by Khadija Manzoor, Nauman U Gilal, Marco Agus, Jens Schneider

“…Methods We propose a two-phase framework: (i) Precise instance segmentation using U-Net with a Visual Geometry Group (VGG16 encoder) to isolate skin lesions and (ii) classification using EfficientFormer and SwiftFormer networks to evaluate performance on both balanced and imbalanced datasets. …”
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Identification of NAPL Contamination Occurrence States in Low-Permeability Sites Using UNet Segmentation and Electrical Resistivity Tomography by Mengwen Gao, Yu Xiao, Xiaolei Zhang

“…Taking an industrial site in Shanghai as the research object, we collected apparent resistivity data using the WGMD-9 system, obtained resistivity profiles through inversion imaging, and constructed training sets by generating contamination labels via K-means clustering. …”
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U-net with ResNet-34 backbone for dual-polarized C-band baltic sea-ice SAR segmentation by Juha Karvonen

“…Sentinel-1 Extra Wide Swath mode HH/HV-polarized SAR data acquired during the winter season 2018–2019, and corresponding segments derived from the daily Baltic Sea ice charts were used for training the segmentation algorithm. …”
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High-quality one-shot interactive segmentation for remote sensing images via hybrid adapter-enhanced foundation models by Zhili Zhang, Xiangyun Hu, Yue Yang, Bingnan Yang, Kai Deng, Hengming Dai, Mi Zhang

“…Interactive segmentation of remote sensing images enables the rapid generation of annotated samples, providing training samples for deep learning algorithms and facilitating high-quality extraction and classification for remote sensing objects. …”
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Research on Simultaneous Localization and Intrusion Detection Methodology for Intelligent Trains Based on Multisource Fusion by ZENG Xiang, JIANG Guotao, LYU Yu, LI Cheng, PAN Wenbo, LUO Ziqi

“…Subsequently, a visual inspection technique is applied to classify objects from images. …”
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Parallel VMamba and Attention-Based Pneumonia Severity Prediction from CXRs: A Robust Model with Segmented Lung Replacement Augmentation by Bouthaina Slika, Fadi Dornaika, Karim Hammoudi

“…<b>Background/Objectives:</b> Rapid and accurate assessment of lung diseases, like pneumonia, is critical for effective clinical decision-making, particularly during pandemics when disease progression can be severe. …”
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