Synergizing natural visual features and 3D building models for robust indoor localization in mixed reality environments by Zhenyu Liu, Christoph Blut, Jörg Blankenbach

“…A main challenge of MR is to accurately align (register) virtual information or objects to the real world, which is a prerequisite for a good visualization and immersive experience. This paper introduces a visual localization method for MR based on the natural feature door and as-planned Building Information Modeling (BIM) models as reference data. …”
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Real-time early corn and weed classification using hybrid visual features based on parallel processing and tracking by Faisal Dharma Adhinata, Wahyono, Raden Sumiharto

“…The speed of video processing is also supported by the machine learning method. The combination of visual features through feature selection is also applied in this research. …”
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Facial expression morphing: enhancing visual fidelity and preserving facial details in CycleGAN-based expression synthesis by Chayanon Sub-r-pa, Rung-Ching Chen, Ming-Zhong Fan

“…To address this issue, we introduce the Facial Expression Morphing (FEM) algorithm, a novel post-processing method designed to enhance the visual fidelity of CycleGAN-based outputs. …”
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Revealing the Relationship Between Urban Park Landscape Features and Visual Aesthetics by Deep Learning-Driven and Spatial Analysis by Jiaxuan Shi, Lyu Mei, Yumeng Meng, Weijun Gao

“…Five urban parks were chosen to evaluate landscape visual quality by using the Scenic Beauty Estimation (SBE) method. …”
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Multimodal learning audio-visual detection for obtaining object-level sound sources in Japanese-language teaching room by Lu Li, Xiuxiu Bai, Junxiu Xu, Dingkang Wang, Tao Jiang

“…This study proposes a novel deep learning-based approach for audio-visual detection (AVD) in Japanese-language teaching rooms, combining audio and visual information to detect sound sources at the object level. …”
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PLY-SLAM: Semantic Visual SLAM Integrating Point–Line Features with YOLOv8-seg in Dynamic Scenes by Huan Mao, Jingwen Luo

“…In dynamic and low texture environments, traditional point-feature-based visual SLAM (vSLAM) often faces the challenges of poor robustness and low localization accuracy. …”
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Ensemble of deep learning and IoT technologies for improved safety in smart indoor activity monitoring for visually impaired individuals by Mesfer Al Duhayyim

“…These solutions improve quality of life by promoting independence while providing peace of mind to loved ones and caregivers. Visual impairment challenges daily independence, and deep learning (DL)-based Human Activity Recognition (HAR) enhances safe, real-time task performance for the visually impaired. …”
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Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection by Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin

“…This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio jets are deflected by the intracluster medium. A combined method, which involves a deep learning-based radio source finder along with visual inspection, has been utilized to search for BTRGs from the Faint Images of the Radio Sky at Twenty cm survey images. …”
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Central Dioptric Line Image-Based Visual Servoing for Nonholonomic Mobile Robot Corridor-Following and Doorway-Passing by Chen Zhong, Qingjia Kong, Ke Wang, Zhe Zhang, Long Cheng, Sijia Liu, Lizhu Han

“…In this paper, we propose a novel nonholonomic mobile robot corridor-following and doorway-passing method based on image-based visual servoing (IBVS) by using a single dioptric camera. …”
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Visualizing the three-dimensional shape of a high-energy particle beam using a position-sensitive photodiode by M. Yoshino, T. Uchida, Y. Nikkawa, S. Saito, Y. Shiina, Y. Nakano

“…We describe a simple and robust method for particle beam visualization using a general-purpose position-sensitive photodiode as a time- and position-sensitive particle detector. …”
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A Multi-Criteria Perceptual Visual Complexity Metrics-Based Optimization Approach to User Interface Design Layouts by Eren Akca, Omer Ozgur Tanriover, Asim Egemen Yilmaz

“…To this aim, we developed a method that relies on perceptual visual complexity metrics specifically, alignment, balance, density and an introduced measure called distance to focal area. …”
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Persepsi Visual Fasad Bangunan di Kawasan Taman Ismail Marzuki Jakarta Sebagai Pembentuk Citra Kawasan by Annisa Tjahya Fitrianty, Herry Santosa, Jenny Ernawati

“…Challenges related to the visual aspects of the urban environment arise from the diverse interests, abilities, and perceptions of the community. …”
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The impact of new high-rise buildings on visual preference of historic districts: a case study of Shenyang, China by Xinlingyi Huang, Xuefeng Zhao

“…And the relative height, relative mass ratio, and relative distance ratio of new high-rise buildings are all influential factors in the public’s visual preference for historic districts. In addition, the range of these variables also has an effect on visual preference. …”
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Analysis of Additional Building Effects in Historic Buildings with Visual Attention Software: The Case of Dresden Military History Museum by Nuray ÖZKARACA ÖZALP, Hicran Hanım HALAÇ

“…This assumption constitutes the hypothesis of the study. In the study, the visual attention method was used to analyze the additional building effects in historical buildings. …”
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A Rare Case of Monocular Visual Loss after Spinal Surgery in Prone Position with Adequate Eye Protection by Naresh Kannan Babu, Piyush Kohli, Suresh Palaniappan, Ilango Krishnamurthi, Kim Ramasamy

“…The aim of this case report is to present a rare case of monocular visual loss after spinal surgery in prone position with adequate eye protection. …”
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CompGO: an R package for comparing and visualizing Gene Ontology enrichment differences between DNA binding experiments by Ashley J. Waardenberg, Bassett Maya, Romaric Bouveret, Richard P. Harvey

“…Results Herein, we present a bioinformatics tool, CompGO, for identifying Differentially Enriched Gene Ontologies, called DiEGOs, and pathways, through the use of a z-score derivation of log odds ratios, and visualizing these differences at GO and pathway level. …”
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A novel strategy for predicting the quality of a base liquor: visual detection of functional bacteria and its application by Lijuan Yin, Lijing Sun, Yueqi Wang, Gailing Shi, Liangcai Lin, Cuiying Zhang

“…To quantitatively evaluate the concentration of A. jinshanensis in the fermentation system, a CRISPR/Cas12a-coupled gold nanoparticle visual biosensor was developed. The limit of detection for A. jinshanensis was as low as 1 copy/μL, and its sensitivity exceeded that of the existing quantitative real-time PCR method. …”
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Accurate and Robust Train Localization: Fusing Degeneracy-Aware LiDAR-Inertial Odometry and Visual Landmark Correction by Lin Yue, Peng Wang, Jinchao Mu, Chen Cai, Dingyi Wang, Hao Ren

“…To overcome the limitations of current train positioning systems, including low positioning accuracy and heavy reliance on track transponders or GNSS signals, this paper proposes a novel LiDAR-inertial and visual landmark fusion framework. Firstly, an IMU preintegration factor considering the Earth’s rotation and a LiDAR-inertial odometry factor accounting for degenerate states are constructed to adapt to railway train operating environments. …”
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Investigation of Personalized Visual Stimuli via Checkerboard Patterns Using Flickering Circles for SSVEP-Based BCI System by Nannaphat Siribunyaphat, Natjamee Tohkhwan, Yunyong Punsawad

“…The second study utilizes personalized visual stimuli to enhance SSVEP responses. SSVEP detection was performed using power spectral density (PSD) analysis by employing Welch’s method and relative PSD to extract SSVEP features. …”
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Visual delta generation with large multi-modal models enhances composed image retrieval using unlabeled data by Young Kyun Jang, Donghyun Kim

“…To address this, we propose a new approach and settings where we identify a reference image and its associated target images in auxiliary image data. Our method involves training a large language model-based Visual Delta Generator (VDG) to produce textual descriptions of the visual differences (i.e., visual deltas) between these images. …”
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