Human-Machine Interface for a Smart Wheelchair by Amiel Hartman, Vidya K. Nandikolla

“…The on board computer system is evaluated for cluster processing performance for the smart wheelchair, incorporating camera machine vision and LiDAR perception for terrain obstacle detection, operating in urban scenarios.…”
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New Trends in Robotics for Agriculture: Integration and Assessment of a Real Fleet of Robots by Luis Emmi, Mariano Gonzalez-de-Soto, Gonzalo Pajares, Pablo Gonzalez-de-Santos

“…Computer-based sensors and actuators such as global positioning systems, machine vision, and laser-based sensors have progressively been incorporated into mobile robots with the aim of configuring autonomous systems capable of shifting operator activities in agricultural tasks. …”
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NF-GAT: A Node Feature-Based Graph Attention Network for ASD Classification by Shuaiqi Liu, Beibei Liang, Siqi Wang, Bing Li, Lidong Pan, Shui-Hua Wang

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Digital maturity of the Russian metallurgical industry: drivers and challenges of growth in new geopolitical conditions. Part II. Key directions of digital transformation by I. S. Prokhorova, V. S. Ustinov, A. V. Elkhova

“…The key areas of digital transformation are digital twins, machine vision and artificial intelligence, the creation of metal products and secondary raw materials marketplaces, which corresponds to the global digitalization trend. …”
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A Fatigue Driving Detection Algorithm Based on Facial Motion Information Entropy by Feng You, Yunbo Gong, Haiqing Tu, Jianzhong Liang, Haiwei Wang

“…Research studies on machine vision-based driver fatigue detection algorithm have improved traffic safety significantly. …”
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Enhanced image processing and storage for defect evaluation in BIM of inspected steel bridges by Dogan Karluklu, Cecilia Rinaldi, Marianna Crognale, Lucia Figuli, Vincenzo Gattulli

“…The authors table a procedure that can be followed, starting with storing defect images and ending with defect visualization in the BIM environment, and present a discussion on the advantages and limits of the process by examining concepts such as automated data collection by drones, machine vision-based damage identification by color detection technique, BIM and Industry Foundation Classes standardisation applied to inspection data.…”
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Potato Quality Grading Based on Depth Imaging and Convolutional Neural Network by Qinghua Su, Naoshi Kondo, Dimas Firmanda Al Riza, Harshana Habaragamuwa

“…As a cost-effective and nondestructive detection method, the machine vision technology has been widely applied in the detection of potato defects. …”
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Enhancing spectral imaging with multi-condition image fusion by Joana Teixeira, Tomás Lopes, Diana Capela, Catarina S. Monteiro, Diana Guimarães, Alexandre Lima, Pedro A. S. Jorge, Nuno A. Silva

“…This significantly expands the accessible information compared to conventional imaging approaches such as machine vision. However, despite its potential, spectral imaging also faces specific challenges depending on the limitations of the spectroscopy technique used, such as signal saturation, matrix interferences, fluorescence, or background emission. …”
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A lung nodule segmentation model based on the transformer with multiple thresholds and coordinate attention by Tianjiao Hu, Yihua Lan, Yingqi Zhang, Jiashu Xu, Shuai Li, Chih-Cheng Hung

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Adaptive coordinated control for an under-actuated airplane–tractor system with parameter uncertainties by Pengjie Xu, Weining Huang, Tianrui Zhao, Wei Zhang, Tongwei Lu, Guiyan Qiang, Lin Zhang, Yanzheng Zhao

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Application and Analyzation of the Vision-Based Structure Model Displacement Measuring Method in Cassette Structure Shaking Table Experiment by Wang Yanhua, Wang Cheng, Feng Yan, Dai Bowen, Wu Gang

“…A Python-OpenCV-based structural calculation program combining computer vision and machine vision is developed to extract and calculate the displacement of the artificial targets from the series of the images acquired. …”
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Measurement of Seed Cotton Color Using RGB Imaging and Color-Unet by Hao Li, Qingxu Li, Wanhuai Zhou, Ruoyu Zhang, Shicheng Hong, Mengyun Zhang, Zhiqiang Zhai

“…First, a color detection system utilizing machine vision technology was developed to capture seed cotton images. …”
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TAD: A Large-Scale Benchmark for Traffic Accidents Detection From Video Surveillance by Yajun Xu, Huan Hu, Chuwen Huang, Yibing Nan, Yuyao Liu, Kai Wang, Zhaoxiang Liu, Shiguo Lian

“…Automatic traffic accident detection has attracted the attention of the machine vision community for the rapid development of autonomous intelligent transportation systems (ITS). …”
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Galaxy evolution in the post-merger regime. III -- The triggering of active galactic nuclei peaks immediately after coalescence by Sara Ellison, Leonardo Ferreira, Robert Bickley, Tess Grindlay, Samir Salim, Shoshannah Byrne-Mamahit, Shobita Satyapal, David R. Patton, Jillian M. Scudder

“…The Multi-Model Merger Identifier (MUMMI) machine vision pipeline has been demonstrated to provide reliable predictions of time post-merger (T_PM) for galaxies selected from the Ultraviolet Near Infrared and Optical Northern Survey (UNIONS) up to T_PM=1.76 Gyr after coalescence. …”
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Enhancing Agricultural Disease Detection: A Multi‐Model Deep Learning Novel Approach by Muhammad Khalid Hamid, Said Khalid Shah, Ghassan Husnain, Yazeed Yasin Ghadi, Shahab Ahmad Al Maaytah, Ayman Qahmash

“…The findings indicate that the proposed multi‐model approach allows a scalable, non‐invasive, and contactless machine vision solution for the early detection of diseases in plant leaves, achieving an efficiency of 99% via multimodal classification techniques that incorporate statistical variables including mean, median, mode, skewness, and kurtosis.…”
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Lesion classification and diabetic retinopathy grading by integrating softmax and pooling operators into vision transformer by Chong Liu, Weiguang Wang, Jian Lian, Wanzhen Jiao

“…Therefore, plenty of automated screening technique have been developed to address this task.MethodsAmong these techniques, the deep learning models have demonstrated promising outcomes in various types of machine vision tasks. However, most of the medical image analysis-oriented deep learning approaches are built upon the convolutional operations, which might neglect the global dependencies between long-range pixels in the medical images. …”
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Research Status and Prospects of Key Technologies for Rice Smart Unmanned Farms by YU Fenghua, XU Tongyu, GUO Zhonghui, BAI Juchi, XIANG Shuang, GUO Sien, JIN Zhongyu, LI Shilong, WANG Shikuan, LIU Meihan, HUI Yinxuan

“…Rice storage and processing quality detection technology mainly utilizes spectral technology and machine vision technology to detect spectra and images, and future research can combine deep learning and multimodal fusion technology to improve the machine vision system's ability and adaptability to recognize the appearance characteristics of rice.…”
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SRADHO: statistical reduction approach with deep hyper optimization for disease classification using artificial intelligence by G. Sathish Kumar, E. Suganya, S. Sountharrajan, Balamurugan Balusamy, Adil O. Khadidos, Alaa O. Khadidos, Shitharth Selvarajan

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Seedling Stage Corn Line Detection Method Based on Improved YOLOv8 by LI Hongbo, TIAN Xin, RUAN Zhiwen, LIU Shaowen, REN Weiqi, SU Zhongbin, GAO Rui, KONG Qingming

“…[Methods]The proposed method employs machine vision techniques to address common field challenges. …”
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Critical band-to-band-tunnelling based optoelectronic memory by Hangyu Xu, Runzhang Xie, Jinshui Miao, Zhenhan Zhang, Haonan Ge, Xuming Shi, Min Luo, Jinjin Wang, Tangxin Li, Xiao Fu, Johnny C. Ho, Peng Zhou, Fang Wang, Weida Hu

“…Abstract Neuromorphic vision hardware, embedded with multiple functions, has recently emerged as a potent platform for machine vision. To realize memory in sensor functions, reconfigurable and non-volatile manipulation of photocarriers is highly desirable. …”
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