The effects of lutein/ zeaxanthin (Lute-gen®) on eye health, eye strain, sleep quality, and attention in high electronic screen users: a randomized, double-blind, placebo-controlle... by A. L. Lopresti, A. L. Lopresti, S. J. Smith

“…Outcome measures included several ophthalmic examinations comprising the Schirmer tear test, photo-stress recovery time, contrast sensitivity, tear film break-up time, and self-report measures of visual fatigue, computer vision, sleep quality and attention.ResultsCompared to the placebo, lutein and zeaxanthin supplementation was associated with greater improvements in the Schirmer tear test, photo-stress recovery time, and tear film break-up time. …”
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Three-Dimensional Diffusion Model in Sports Dance Video Human Skeleton Detection and Extraction by Zhi Li

“…With the continuous updating of diffusion model acquisition equipment, the rapid development of 3D reconstruction technology, and the continuous enhancement of computing power, the research on the application of 3D diffusion model in the detection and extraction of a human skeleton in sports dance videos has become a hot direction in the field of computer vision and computer graphics. Among them, the feature detection description and model alignment of 3D nonrigid models are a fundamental problem with very important research value and significance and challenging at the same time, which has received wide attention from the academic community.…”
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Automated Measurement of Air Bubbles Dispersion in Ice Cream Using Machine Learning Methods by Igor A. Korolev

“…It can be found in public domain, and researchers are free to adapt it to solve various computer vision issues.…”
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Enhanced multivariate data fusion and optimized algorithm for comprehensive quality profiling and origin traceability of Chinese jujube by Peng Chen, Xiaoli Wang, Rao Fu, Xiaoyan Xiao, Yu Li, Tulin Lu, Tao Wang, Qiaosheng Guo, Peina Zhou, Chenghao Fei

“…This research utilized computer vision, ultrafast gas-phase electronic nose, and GC–MS technologies to collect jujube samples from various regions in China, including Xinjiang, Gansu, Shaanxi, Henan, Shandong, and Hebei. …”
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Bounded multivariate contaminated normal mixture model with applications to skin cancer detection by Abbas Mahdavi

“…The model is well-suited for computer vision and pattern recognition problems due to its heavily-tailed and bounded nature, providing flexibility in modeling data in the presence of outliers. …”
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Perceiving Excitation Characteristics from Interactions between Field Road and Vehicle via Vibration Sensing by Yuansheng Cheng, Xiaoqin Li, Xiaolan Man, Feifan Fan, Zhixiong Li

“…A camera-accelerator system can solve this issue by utilizing computer vision information; however, the relationship between the field road surface and the vehicle vibration response remains an unsolved problem. …”
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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

“…The proposed dataset together with the experimental results are presented as a new benchmark to improve computer vision research, especially in ITS. The dataset is publicly available at <uri>https://github.com/UnicomAI/UnicomBenchmark/tree/main/TADBench</uri>.…”
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Digital eye strain: prevalence and associated socio-demographic factors among banking assistants in Colombo District, Sri Lanka by Supipi Dissanayake Gunawardana, Dushyanthi Jayawaradana

“…DES was detected using Computer Vision Syndrome Questionnaire (CVS-Q). Selected factors were cross-tabulated by the presence or absence of DES and the association was assessed using Chi-squared followed by multiple logistic regression. …”
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Deep Spatio-Temporal Illuminant Estimation Under Time-Varying AC Lights by Jun-Sang Yoo, Kang-Kyu Lee, Chan-Ho Lee, Ji-Min Seo, Jong-Ok Kim

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Oriented R-CNN With Disentangled Representations for Product Packaging Detection by Jiangyi Pan, Jianjun Yang, Yinhao Liu, Yijie Lv

“…Object detection is a vital task in the field of computer vision for various applications such as face detection, autonomous driving and industrial production. …”
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Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network by Raghavendra S, Souvik Ganguli, P. Thirumarai Selvan, Mitali Madhusmita Nayak, Sushovan Chaudhury, Randell U. Espina, Isaac Ofori

“…Deep learning has recently been hailed as the most advanced computer vision technology for image classification. The invention of convolutional neural network (CNN) simplified the effort of feature engineering. …”
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Object Placement Across Robotics, Image Composition, and XR: A Mixed Reality Framework Proposal by Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi

“…Object placement, a critical task involving the optimal positioning, scaling, and orientation of objects within a given environment, is vital across multiple domains, including robotics, computer vision, and virtual/augmented/mixed reality (VR/AR/MR). …”
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A review of deep learning in blink detection by Jianbin Xiong, Weikun Dai, Qi Wang, Xiangjun Dong, Baoyu Ye, Jianxiang Yang

“…Blink detection is a highly concerned research direction in the field of computer vision, which plays a key role in various application scenes such as human-computer interaction, fatigue detection and emotion perception. …”
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Adversarial examples defense method based on multi-dimensional feature maps knowledge distillation by Baolin QIU, Ping YI

“…The neural network approach has been commonly used in computer vision tasks.However, adversarial examples are able to make a neural network generate a false prediction.Adversarial training has been shown to be an effective approach to defend against the impact of adversarial examples.Nevertheless, it requires high computing power and long training time thus limiting its application scenarios.An adversarial examples defense method based on knowledge distillation was proposed, reusing the defense experience from the large datasets to new classification tasks.During distillation, teacher model has the same structure as student model and the feature map vector was used to transfer experience, and clean samples were used for training.Multi-dimensional feature maps were utilized to enhance the semantic information.Furthermore, an attention mechanism based on feature map was proposed, which boosted the effect of distillation by assigning weights to features according to their importance.Experiments were conducted over cifar100 and cifar10 open-source dataset.And various white-box attack algorithms such as FGSM (fast gradient sign method), PGD (project gradient descent) and C＆amp;W (Carlini-Wagner attack) were applied to test the experimental results.The accuracy of the proposed method on Cifar10 clean samples exceeds that of adversarial training and is close to the accuracy of the model trained on clean samples.Under the PGD attack of L2 distance, the efficiency of the proposed method is close to that of adversarial training, which is significantly higher than that of normal training.Moreover, the proposed method is a light-weight adversarial defense method with low learning cost.The computing power requirement is far less than that of adversarial training even if optimization schemes such as attention mechanism and multi-dimensional feature map are added.Knowledge distillation can learn the decision-making experience of normal samples and extract robust features as a neural network learning scheme.It uses a small amount of data to generate accurate and robust models, improves generalization, and reduces the cost of adversarial training.…”
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Person Detection for an Orthogonally Placed Monocular Camera by Pavel Skrabanek, Petr Dolezel, Zdenek Nemec, Dominik Stursa

“…The first approach is the utilization of an appropriate convolutional neural network (ConvNet), which is currently the prevailing approach in computer vision. The second approach is the utilization of histograms of oriented gradients (HOG) features in combination with a support vector machine classifier. …”
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Determination of the area index of lettuce leaves with a monocular camera by Laimonas Kairiūkštis, Başak Yalçıner, Emre Özkul

“…This study showcases the potential of computer vision and machine learning algorithms in transforming traditional agricultural practices into more efficient and data-driven processes. …”
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Enhancing Aquaculture Net Pen Inspection: A Benchmark Study on Detection and Semantic Segmentation by Waseem Akram, Ahsan Baidar Bakht, Muhayy Ud Din, Lakmal Seneviratne, Irfan Hussain

“…Detection and segmentation are computer vision techniques that offer a promising approach to automating these inspections by enabling precise identification and classification of various components within underwater images. …”
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Transforming traffic accident investigations: a virtual-real-fusion framework for intelligent 3D traffic accident reconstruction by Yanzhan Chen, Qian Zhang, Fan Yu

“…This study proposes a novel virtual-real-fusion simulation framework that integrates traffic accident generation, unmanned aerial vehicle (UAV)-based image collection, and a 3D traffic accident reconstruction pipeline with advanced computer vision techniques and unsupervised 3D point cloud clustering algorithms. …”
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Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System by Galib Muhammad Shahriar Himel, Md. Masudul Islam, Kh. Abdullah Al-Aff, Shams Ibne Karim, Md. Kabir Uddin Sikder

“…In recent years, deep learning models have shown remarkable success in various computer vision tasks, including image classification. …”
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A Review on Person Re-Identification Techniques and Its Analysis by C. Selvan, H. Anwar Basha, K. Meenakshi, Soumyalatha Naveen

“…Person re-identification (Re-ID) emerges as a captivating realm within computer vision, dedicated to the task of recognizing the same individual across diverse camera angles or locations. …”
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