Towards Understanding the Security of Modern Image Captchas and Underground Captcha-Solving Services by Haiqin Weng, Binbin Zhao, Shouling Ji, Jianhai Chen, Ting Wang, Qinming He, Raheem Beyah

“…However, the ever-advancing capabilities of computer vision have gradually diminished the security of image captchas and made them vulnerable to attack. …”
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Annotated image dataset with different stages of European pear rust for UAV-based automated symptom detection in orchardsMendeley Data by Virginia Maß, Pendar Alirezazadeh, Johannes Seidl-Schulz, Matthias Leipnitz, Eric Fritzsche, Rasheed Ali Adam Ibraheem, Martin Geyer, Michael Pflanz, Stefanie Reim

“…Each leaf with pear rust symptoms was annotated with the drawing method by two points (bounding boxes) using the Computer Vision Annotation Tool (CVAT, v1.1.0) [1] and presented in YOLO 1.1 file format (.txt files). …”
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Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future by Vasileios Leivaditis, Eleftherios Beltsios, Athanasios Papatriantafyllou, Konstantinos Grapatsas, Francesk Mulita, Nikolaos Kontodimopoulos, Nikolaos G. Baikoussis, Levan Tchabashvili, Konstantinos Tasios, Ioannis Maroulis, Manfred Dahm, Efstratios Koletsis

“…Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. …”
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Future of artificial intelligence for the diagnosis and treatment of retinal diseases by E.A. Katalevskaya, D.Yu. Katalevskiy, M.I. Tyurikov, I.A. Velieva, A.V. Bol’shunov

“…</i> </p> <p> <i><b>Keywords</b>: artificial intelligence, computer vision, ophthalmic screening, diabetic retinopathy, diabetic macular edema, age-related macular degeneration.…”
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A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching by Jose Moises Araya-Martinez, Jose Moises Araya-Martinez, Vinicius Soares Matthiesen, Vinicius Soares Matthiesen, Simon Bøgh, Jens Lambrecht, Rui Pimentel de Figueiredo

“…Object pose estimation is essential for computer vision applications such as quality inspection, robotic bin picking, and warehouse logistics. …”
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cigFacies: a massive-scale benchmark dataset of seismic facies and its application by H. Gao, X. Wu, X. Sun, M. Hou, M. Hou, H. Gao, G. Wang, H. Sheng

“…Data-driven deep-learning approaches are highly promising for automating the seismic facies classification with high efficiency and accuracy, as they have already achieved significant success in similar image classification tasks within the field of computer vision (CV). However, unlike the CV domain, the field of seismic exploration lacks a comprehensive benchmark dataset for seismic facies, severely limiting the development, application, and evaluation of deep-learning approaches in seismic facies classification. …”
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ViTAU: Facial paralysis recognition and analysis based on vision transformer and facial action units by Jia GAO, Wenhao CAI, Junli ZHAO, Fuqing DUAN

“…With the rapid advancement of deep learning and computer vision technologies, automatic recognition of facial paralysis has become feasible, offering a more accurate and objective diagnostic approach. …”
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Enhancement of convolutional neural network for urban environment parking space classification by S. Rahman, M. Ramli, F. Arnia, R. Muharar, M. Ikhwan, S. Munzir

“…Modification of the Convolutional Neural Networks architecture is assumed to increase the work efficiency of the smart parking system in processing parking availability information.METHODS: Research is focusing on developing parking space classification techniques using camera sensors due to the rapid advancement of technology and algorithms in computer vision. The input image has 3x3 dimensions. The first convolution layer accepts the input image and converts it into 56x56 dimensions. …”
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Perbandingan Kinerja Inception- Resnetv2, Xception, Inception-v3, dan Resnet50 pada Gambar Bentuk Wajah by Fitriana Masruroh, Bayu Surarso, Budi Warsito

“…Deep learning is becoming a trend in the field of computer vision because it gives the best results than the previous method. …”
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An Open-Source Multi-Robot Framework System for Collaborative Environments Based on ROS2 by Francisco Yumbla, Marcelo Fajardo-Pruna, Anthonny Piguave, Diego Ronquillo, Ricardo Ortiz, Jongseong Brad Choi, Gabriel Diaz, Xabiel G. Paneda, Hyungpil Moon

“…A centralized architecture was obtained with an autonomous navigation module for the planning and robot routes monitoring, a computer vision module for the location and management of uncertainties, and a task controller module to assign mobilization mission objects. …”
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Can ChatGPT4-vision identify radiologic progression of multiple sclerosis on brain MRI? by Brendan S. Kelly, Sophie Duignan, Prateek Mathur, Henry Dillon, Edward H. Lee, Kristen W. Yeom, Pearse A. Keane, Aonghus Lawlor, Ronan P. Killeen

“…However, in absolute terms, in a simplified “spot the difference” medical imaging task, GPT4V was inferior to state-of-the-art computer vision methods. GPT4V’s performance metrics were more similar to the ViT than the U-net. …”
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Klasifikasi Aktivitas Manusia Menggunakan Algoritme Computed Input Weight Extreme Learning Machine dengan Reduksi Dimensi Principal Component Analysis by M. Sofyan Irwanto, Fitra A. Bachtiar, Novanto Yudistira

“…Based on various approaches that have been used to recognize human activity, sensor-based techniques are known to be superior to other techniques such as computer vision-based techniques. Sensor-based technique can also be performed using smartphones, but smartphone has disadvantages in performing complex alghorithmic computation. …”
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Iterative optimization annotation pipeline and ALSS-YOLO-Seg for efficient banana plantation segmentation in UAV imagery by Ang He, Ang He, Ximei Wu, Ximei Wu, Xing Xu, Xing Xu, Jing Chen, Jing Chen, Xiaobin Guo, Xiaobin Guo, Sheng Xu, Sheng Xu

“…Our code is openly available at https://github.com/helloworlder8/computer_vision.…”
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AI-assisted detection for chest X-rays (AID-CXR): a multi-reader multi-case study protocol by Fergus Gleeson, Alex Novak, Indrajeet Das, Ruchir Shah, Edwin van Beek, Sarim Ather, Howell Fu, Nabeeha Salik, Alan Campbell, Farhaan Khan, Abdala Trinidad Espinosa Morgado, Marusa Kotnik, Louise Wing, John Murchison, Jong Seok Ahn, Sang Hyup Lee, Ambika Seth

“…Advances in machine learning and computer vision technologies have led to the development of several artificial intelligence (AI) tools to detect abnormalities on CXRs, which may expand diagnostic support to a wider field of health professionals. …”
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Automated Video Assistant Referee in Lead Climbing by Eliane Künzler, David Roder, Urs Stöcker, Peter Wolf

“…RTMO: Towards high-performance one-stage real-time multi-person pose estimation. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 1491–1500. https://doi.org/10.1109/CVPR52733.2024.00148 …”
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PHARAOH: A collaborative crowdsourcing platform for phenotyping and regional analysis of histology by Kevin Faust, Min Li Chen, Parsa Babaei Zadeh, Dimitrios G. Oreopoulos, Alberto J. Leon, Ameesha Paliwal, Evelyn Rose Kamski-Hennekam, Marly Mikhail, Xianpi Duan, Xianzhao Duan, Mugeng Liu, Narges Ahangari, Raul Cotau, Vincent Francis Castillo, Nikfar Nikzad, Richard J. Sugden, Patrick Murphy, Safiyh S. Aljohani, Philippe Echelard, Susan J. Done, Kiran Jakate, Zaid Saeed Kamil, Yazeed Alwelaie, Mohammed J. Alyousef, Noor Said Alsafwani, Assem Saleh Alrumeh, Rola M. Saleeb, Maxime Richer, Lidiane Vieira Marins, George M. Yousef, Phedias Diamandis

“…Here, we present an online collaborative platform that streamlines tissue image annotation to promote the development and sharing of custom computer vision models for PHenotyping And Regional Analysis Of Histology (PHARAOH; https://www.pathologyreports.ai/ ). …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…Object detection (OD) is an essential task in computer vision. Although state-of-the-art deep learning-based OD methods achieve high detection rates, their large model size and high computational demands often hinder deployment on resource-constrained edge devices. …”
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Convolutional neural networks for sea surface data assimilation in operational ocean models: test case in the Gulf of Mexico by O. Zavala-Romero, O. Zavala-Romero, A. Bozec, E. P. Chassignet, J. R. Miranda, J. R. Miranda

“…<p>Deep learning models have demonstrated remarkable success in fields such as language processing and computer vision, routinely employed for tasks like language translation, image classification, and anomaly detection. …”
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Rice Leaf Disease Image Enhancement Based on Improved CycleGAN by YAN Congkuan, ZHU Dequan, MENG Fankai, YANG Yuqing, TANG Qixing, ZHANG Aifang, LIAO Juan

“…Automatic recognition of rice diseases using computer vision is crucial for ensuring high yields, quality, and efficiency. …”
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Preparation and physicochemical/antimicrobial characteristics of asparagus cellulose films containing quercetin by Tao Jin, Ling Yan, Wei Liu, Shuai Liu, Changhong Liu, Lei Zheng

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