Relevant bibliographies by topics / Yolo (you only look once)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Yolo (you only look once)'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Yolo (you only look once)"

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Arifadilah, Daffa, Asriyanik, and Agung Pambudi. "Sunda Script Detection Using You Only Look Once Algorithm." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 3, no. 2 (2024): 606–13. http://dx.doi.org/10.59934/jaiea.v3i2.443.

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The Sundanese script is a writing system used in the Sundanese language, one of the regional languages of West Java, Indonesia. This study investigates the use of the YOLO v8 algorithm for the real-time video detection of Sundanese script. Various versions of YOLO v8, including YOLO v8n, v8s, v8m, v8l, and v8x, were tested to determine the most effective model. After a comprehensive evaluation involving the analysis of mean Average Precision (mAP), F1-Confidence, and precision, the study selected the YOLO v8s model as the primary detection method. YOLO v8s demonstrated superior performance wit
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Anorbaev, Akmal, Prerna Agarwal, and Pranav Shrivastava. "You Only Look Once (YOLO): Object Detection Algorithm." International Journal of Computer Applications ICAIDSC2023, no. 3 (2025): 9–14. https://doi.org/10.5120/icaidsc202419.

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Huangfu, Zhongmin, and Shuqing Li. "Lightweight You Only Look Once v8: An Upgraded You Only Look Once v8 Algorithm for Small Object Identification in Unmanned Aerial Vehicle Images." Applied Sciences 13, no. 22 (2023): 12369. http://dx.doi.org/10.3390/app132212369.

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In order to solve the problems of high leakage rate, high false detection rate, low detection success rate and large model volume of small targets in the traditional target detection algorithm for Unmanned Aerial Vehicle (UAV) aerial images, a lightweight You Only Look Once (YOLO) v8 algorithm model Lightweight (LW)-YOLO v8 is proposed. By increasing the channel attention mechanism Squeeze-and-Excitation (SE) module, this method can adaptively improves the model’s ability to extract features from small targets; at the same time, the lightweight convolution technology is introduced into the Con
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Andi, Ilham, Mutmainnah Muchtar, and Jayanti Yusmah Sari. "Mask Detection Using the YOLO (You Only Look Once) Method." Jurnal Media Informasi Teknologi 1, no. 1 (2024): 1–12. http://dx.doi.org/10.69616/mit.v1i1.165.

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The COVID-19 pandemic has emphasized the importance of wearing masks as a preventive measure. To facilitate mask detection and ensure compliance, computer vision techniques have been widely utilized. This research aims to develop a mask detection system using the YOLO (You Only Look Once) method. YOLO is a real-time object detection method that provides accurate and efficient results. The proposed system utilizes a pre-trained YOLO model trained on a dataset comprising images of individuals with and without masks. The YOLO model can detect and locate faces, as well as differentiate between ind
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Ovide, Decroly Wisnu Ardhi, Retnaningsih Soeprobowati Tri, Adi Kusworo, Prakasa Esa, and Rachman Arief. "Enhanced you only look once approach for automatic phytoplankton identification." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (2024): 3426–36. https://doi.org/10.11591/ijai.v13.i3.pp3426-3436.

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Conventionally, identifying phytoplankton species is challenging due to human taxonomical knowledge limitations. Advanced technology can overcome this problem. A novel model that accurately enhances phytoplankton detection and identification classification by combining asymmetric convolution and vision transformers (ACVIT) within the YOLOv8m framework is promoted with ACVIT-YOLO. The performance of this model surpasses the original YOLOv8m model, exhibiting a notable 2.4% enhancement in precision, 5.5% improvement in recall, and 1.1% gain in mAP 50 score. The enhanced effectiveness of ACVIT-YO
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Wisnu Ardhi, Ovide Decroly, Tri Retnaningsih Soeprobowati, Kusworo Adi, Esa Prakasa, and Arief Rachman. "Enhanced you only look once approach for automatic phytoplankton identification." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (2024): 3426. http://dx.doi.org/10.11591/ijai.v13.i3.pp3426-3436.

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<p>Conventionally, identifying phytoplankton species is challenging due to human taxonomical knowledge limitations. Advanced technology can overcome this problem. A novel model that accurately enhances phytoplankton detection and identification classification by combining asymmetric convolution and vision transformers (ACVIT) within the YOLOv8m framework is promoted with ACVIT-YOLO. The performance of this model surpasses the original YOLOv8m model, exhibiting a notable 2.4% enhancement in precision, 5.5% improvement in recall, and 1.1% gain in mAP 50 score. The enhanced effectiveness of
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NAGAGOPIRAJU, Dr V., SUVARNA PINNINTI, ANJAMMA TAMMA, SAI TEJA KAJJAYAM, and KALESHAVALI KAKARLA. "ADVANCED WILD ANIMAL DETECTION AND ALERT SYSTEM USING THE YOLO V5 MODEL POWERED BY AI." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 15, no. 1 (2024): 142–45. http://dx.doi.org/10.61841/turcomat.v15i1.14556.

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An advanced wild animal detection and alert system using you only look once version5 (YOLO V5) model. The system utilizes you only look once version5 (YOLO V5) object detection algorithm to identify wild animals and alert users to their presence in real-time. The system employs a camera to capture real-time video, which is then sent to a computer running you only look once version5 (YOLO V5) algorithm. When the system detects a wild animal, it sends an alert to the wild animal by playing any sounds like bullets firing. The system is expected to have a significant impact on the safety of people
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Wijanarko, Restu Gilang, Afu Ichsan Pradana, and Dwi Hartanti. "IMPLEMENTASI DETEKSI DRONE MENGGUNAKAN YOLO (You Only Look Once)." JURNAL FASILKOM 14, no. 2 (2024): 437–42. https://doi.org/10.37859/jf.v14i2.7374.

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Penelitian ini berfokus pada pengembangan sistem deteksi drone yang akurat dan efektif berbasis teknologi kamera. Penggunaan drone yang semakin meningkat di berbagai sektor, seperti fotografi udara, pemantauan lingkungan, pemetaan topografi, pengiriman barang, inspeksi infrastruktur, dan pertanian presisi, telah membawa banyak manfaat. Namun, penggunaan drone yang tidak bertanggung jawab juga dapat menimbulkan masalah serius, seperti pelanggaran privasi, risiko keamanan, dan gangguan pada operasi penerbangan. Untuk mengatasi tantangan ini, penelitian ini mengusulkan pendekatan deteksi drone me
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Mahfudi, Isa, Ahmad Rozak Setia Nugraha, and Azam Muzakhim Imammuddin. "Implementasi You Only Look Once (YOLO) dalam Deteksi Telur Menetas pada Reptil." JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) 6, no. 2 (2024): 177–84. https://doi.org/10.26905/jasiek.v6i2.13525.

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Saat ini reptil dijadikan hewan peliharaan karena perawatan yang mudah dan warna motif yang beragam salah satunya adalah Leopard Gecko. Perawatan Leopard Gecko yang baru menetas berbeda dari yang dewasa karena Leopard Gecko yang baru menetas harus segera ditempatkan di kandang yang diberi alas tisu dan disemprot air untuk menghindari kehilangan air. penelitian ini bertujuan untuk mengembangkan sistem deteksi telur menetas menggunakan YOLO (You Only Look Once). Hasil penelitian menunjukkan bahwa algoritma YOLO dapat digunakan untuk mendeteksi telur Leopard Gecko menetas secara real-time. persen
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Ghozali, Mohammad Shiddiq. "PEMBUATAN PENDETEKSI OBYEK DENGAN METODE YOU ONLY LOOK ONCE (YOLO) UNTUK AUTOMATED TELLER MACHINE (ATM)." Majalah Ilmiah UNIKOM 17, no. 1 (2019): 69–76. http://dx.doi.org/10.34010/miu.v17i1.2225.

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Perkembangan Teknologi Informasi dan Komunikasi begitu pesat di zaman sekarang ini. Diikuti pula dengan perkembangan di bidang Artificial Intelligence (AI) atau Kecerdasan Buatan. Di Indonesia sendiri masih belum begitu populer dikalangan masyarakat akan tetapi perusahaan-perusahaan IT berlomba-lomba menciptakan inovasi dibidang Kecerdasan Buatan dan penerapan Kecerdasan Buatan disegala aspek kehidupan. Contoh kasus di Automated Teller Machine (ATM), seringkali terjadi kejahatan di ATM seperti pengintaian nomor pin, skimming, lebanese loop dan kejahatan lainnya. Walaupun di ATM sudah terdapat
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Dissertations / Theses on the topic "Yolo (you only look once)"

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Lamberti, Lorenzo. "A deep learning solution for industrial OCR applications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19777/.

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This thesis describes a project developed throughout a six months internship in the Machine Vision Laboratory of Datalogic based in Pasadena, California. The project aims to develop a deep learning system as a possible solution for industrial optical character recognition applications. In particular, the focus falls on a specific algorithm called You Only Look Once (YOLO), which is a general-purpose object detector based on convolutional neural networks that currently offers state-of-the-art performances in terms of trade-off between speed and accuracy. This algorithm is indeed well known fo
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Hamren, Rasmus. "APPLYING UAVS TO SUPPORT THE SAFETY IN AUTONOMOUS OPERATED OPEN SURFACE MINES." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-53376.

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Unmanned aerial vehicle (UAV) is an expanding interest in numerous industries for various applications. Increasing development of UAVs is happening worldwide, where various sensor attachments and functions are being added. The multi-function UAV can be used within areas where they have not been managed before. Because of their accessibility, cheap purchase, and easy-to-use, they replace expensive systems such as helicopters- and airplane-surveillance. UAV are also being applied into surveillance, combing object detection to video-surveillance and mobility to finding an object from the air with
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Grahn, Fredrik, and Kristian Nilsson. "Object Detection in Domain Specific Stereo-Analysed Satellite Images." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159917.

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Given satellite images with accompanying pixel classifications and elevation data, we propose different solutions to object detection. The first method uses hierarchical clustering for segmentation and then employs different methods of classification. One of these classification methods used domain knowledge to classify objects while the other used Support Vector Machines. Additionally, a combination of three Support Vector Machines were used in a hierarchical structure which out-performed the regular Support Vector Machine method in most of the evaluation metrics. The second approach is more
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Borngrund, Carl. "Machine vision for automation of earth-moving machines : Transfer learning experiments with YOLOv3." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-75169.

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This master thesis investigates the possibility to create a machine vision solution for the automation of earth-moving machines. This research was done as without some type of vision system it will not be possible to create a fully autonomous earth moving machine that can safely be used around humans or other machines. Cameras were used as the primary sensors as they are cheap, provide high resolution and is the type of sensor that most closely mimic the human vision system. The purpose of this master thesis was to use existing real time object detectors together with transfer learning and exa
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Ali, Hani, and Pontus Sunnergren. "Scenanalys - Övervakning och modellering." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-45036.

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Självkörande fordon kan minska trafikstockningar och minska antalet trafikrelaterade olyckor. Då det i framtiden kommer att finnas miljontals autonoma fordon krävs en bättre förståelse av omgivningen. Syftet med detta projekt är att skapa ett externt automatiskt trafikledningssystem som kan upptäcka och spåra 3D-objekt i en komplex trafiksituation för att senare skicka beteendet från dessa objekt till ett större projekt som hanterar med att 3D-modellera trafiksituationen. Projektet använder sig av Tensorflow ramverket och YOLOv3 algoritmen. Projektet använder sig även av en kamera för att spel
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(8786558), Mehul Nanda. "You Only Gesture Once (YouGo): American Sign Language Translation using YOLOv3." Thesis, 2020.

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<div>The study focused on creating and proposing a model that could accurately and precisely predict the occurrence of an American Sign Language gesture for an alphabet in the English Language</div><div>using the You Only Look Once (YOLOv3) Algorithm. The training dataset used for this study was custom created and was further divided into clusters based on the uniqueness of the ASL sign.</div><div>Three diverse clusters were created. Each cluster was trained with the network known as darknet. Testing was conducted using images and videos for fully trained models of each cluster and</div><div>A
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Books on the topic "Yolo (you only look once)"

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Seabury, Sue. Yolo: You Only Live Once. Independently Published, 2019.

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Aroskar, Dr Shilpa. YOLO You Only Live Once. Platinum Press, 2016.

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Doodle Books by Tickle Tees. YOLO : You Only Live Once Rainbow Inspiration Journal: Get Inspired to Do Great Things! Independently Published, 2020.

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diem, yolo carpe. YOLO, You Only Live Once. Carpe Diem for Stupid People: Notbook Gift Journal 110 Pages 6x9 Inch Coworker Personalized. Independently Published, 2020.

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Weores, Tivadar. Composition Notebook: Yolo You Only Live Once Cookies Gothel Danzig Difficult Mistake Bracelet Mother Notebook Journal Notebook Blank Lined Ruled 6x9 100 Pages. Independently Published, 2020.

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Johansen, Bruce, and Adebowale Akande, eds. Nationalism: Past as Prologue. Nova Science Publishers, Inc., 2021. http://dx.doi.org/10.52305/aief3847.

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Nationalism: Past as Prologue began as a single volume being compiled by Ad Akande, a scholar from South Africa, who proposed it to me as co-author about two years ago. The original idea was to examine how the damaging roots of nationalism have been corroding political systems around the world, and creating dangerous obstacles for necessary international cooperation. Since I (Bruce E. Johansen) has written profusely about climate change (global warming, a.k.a. infrared forcing), I suggested a concerted effort in that direction. This is a worldwide existential threat that affects every living t
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Book chapters on the topic "Yolo (you only look once)"

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Prakash, Immidisetty V., and M. Palanivelan. "A Study of YOLO (You Only Look Once) to YOLOv8." In Algorithms in Advanced Artificial Intelligence. CRC Press, 2024. http://dx.doi.org/10.1201/9781003529231-40.

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Seethalakshmi, Palaparthi, Rao CH Dhawaleswara, Pavuluri Sreekanth Reddy, Vidhyanadh Babu, and S. Nourin. "Detection of lung nodules-using yolo v7: (You Only Look Once)." In Hybrid and Advanced Technologies. CRC Press, 2025. https://doi.org/10.1201/9781003559139-82.

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Dos Reis Pacheco, Manuel Soares, Hadiyanto Hadiyanto, and Ridwan Sanjaya. "Quality Detection Model of Nutmeg (Myristica Fragrans Houtt) Using You Only Look Once (YOLO)." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3250-3_54.

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Hubert, G., and S. Silvia Priscila. "You Only Look Once (YOLO) with Convolution Neural Network (CNN) Classification for Preterm Baby’s Retinopathy Images." In Advancements in Smart Computing and Information Security. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59097-9_27.

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Ou, Xiaolin. "Computer Vision Technology in Cost Monitoring of Construction Projects." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5814-2_50.

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AbstractWith the continuous development of technology, the application of computer vision technology in cost monitoring of construction projects is becoming increasingly important. By utilizing computer vision technology, construction companies can monitor the progress of construction sites, material usage, and allocation of human resources in real-time, thereby better controlling project costs. The application of this technology can not only improve the efficiency of construction projects, but also reduce human errors and waste, which is of great significance for the successful completion of
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Sultan, Zamra, Muhammad Umar Farooq, and Rana Hammad Raza. "Improved Vehicle Logo Detection and Recognition for Complex Traffic Environments Using Deep Learning Based Unwarping of Extracted Logo Regions in Varying Angles." In Digital Interaction and Machine Intelligence. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37649-8_2.

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AbstractIntelligent Traffic Monitoring and Management System (TMMS) is a growing research area as cities infrastructure continues to evolve. Traffic situation is demanding innovative solutions for effective monitoring and management given the complex nature of the urban scenario. A major focus of this research domain is fine-grained vehicles classification that requires detection and recognition of distinct features of vehicles. Some of these features are semantic based while others are appearance based. One such appearance-based feature of a vehicle is its logo. Logo detection helps with iden
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Campos, Filipe, Francisco Gonçalves Cerqueira, Ricardo P. M. Cruz, and Jaime S. Cardoso. "YOLOMM – You Only Look Once for Multi-modal Multi-tasking." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49018-7_40.

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Qiu, Jingting, Feifan Yu, Fengrui Xu, Jiqiang Wang, and Xinmin Chen. "Improved You Only Look Once Model for UAVs/Ships Relative Attitude Detection." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8658-9_21.

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Zhao, Hanyu. "An investigation into the internet marketing strategy of the Chinese film “YOLO (You Only Live Once)”." In Global Dialogue on Media Dynamics, Trends and Perspectives on Public Relations and Communication. CRC Press, 2024. https://doi.org/10.1201/9781003564966-91.

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Swetha, O., and C. Ramachandran. "Counting and Tracking of Vehicles and Pedestrians in Real Time Using You Only Look Once V3." In Data Intelligence and Cognitive Informatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8530-2_69.

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Conference papers on the topic "Yolo (you only look once)"

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Rani, K. Pushpa, Mohammad Arshad, and A. Sangeetha. "Expression of Concern for: Pothole Detection Using YOLO (You Only Look Once) Algorithm." In 2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC). IEEE, 2022. http://dx.doi.org/10.1109/assic55218.2022.10703639.

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Setiawan, Yosua, Muhammad Nurul Puji, and Winda Astuti. "Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification." In 2024 IEEE International Conference on Smart Mechatronics (ICSMech). IEEE, 2024. https://doi.org/10.1109/icsmech62936.2024.10812285.

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Bandyopadhyay, Shaon, Dipankar Dutta, and Sanjoy Pratihar. "A Comprehensive Analysis of Fast-Food Classification Using You Only Look Once (YOLO) Model." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10724136.

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Ucar, Kursad. "An Approach to Improve Object Detection with You Only Look Once (YOLO) and Artificial Neural Networks." In 2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2024. http://dx.doi.org/10.1109/idap64064.2024.10710822.

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Steven, Brandon, Calista Vannia Nathalie, Christoper Gerry Johanes, and Puti Andam Suri. "Comparison Research: YOLO (You Only Look Once) Model for Indonesian Sign Language Detection Reducing Communication Inequalities." In 2024 2nd International Conference on Technology Innovation and Its Applications (ICTIIA). IEEE, 2024. https://doi.org/10.1109/ictiia61827.2024.10761360.

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Setiawan, Foni Agus, Zakiah Aulia Rohmah, and Gibtha Fitri Laxmi. "Indonesian Sign Language (BISINDO) Alphabet Detection Using the You Only Look Once (YOLO) Algorithm Version 8." In 2024 International Conference on Computer, Control, Informatics and its Applications (IC3INA). IEEE, 2024. http://dx.doi.org/10.1109/ic3ina64086.2024.10732209.

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Doong, Kelvin Yih-Yuh, ChenPo Lin, and Sheng-Che Lin. "Full-chip voltage contrast inference using deep learning you only look once: voltage contrast (YOLO-VC)." In Metrology, Inspection, and Process Control XXXIX, edited by Matthew J. Sendelbach and Nivea G. Schuch. SPIE, 2025. https://doi.org/10.1117/12.3051763.

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Hulliyah, Khodijah, Dito Hafidzulrahman, Nenny Anggraini, Luh Kesuma Wardhani, and Muhamad Fardal Akter Min Gali. "Comparison of You Only Look Once (YOLO) Algorithm Version 5 and Version 8 as Object Detection in Hilal Detection." In 2024 12th International Conference on Cyber and IT Service Management (CITSM). IEEE, 2024. https://doi.org/10.1109/citsm64103.2024.10775779.

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Zhan, Dakui, and Khamron Sunat. "You Only Look Once with Clustering Segmentation Module." In 2025 5th International Conference on Advances in Electrical, Electronics and Computing Technology (EECT). IEEE, 2025. https://doi.org/10.1109/eect64505.2025.10966947.

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Aminuddin, Nurhanisah, Nor Azuana Ramli, and Agus Pratondo. "Real-Time Personal Protective Equipment Compliance Detection Using You Only Look Once." In 2024 5th International Conference on Artificial Intelligence and Data Sciences (AiDAS). IEEE, 2024. http://dx.doi.org/10.1109/aidas63860.2024.10730560.

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Reports on the topic "Yolo (you only look once)"

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Cheng, DingXin. Development of the Roadway Pothole Management Program. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2306.

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Addressing the issue of potholes is a primary concern for maintaining urban infrastructure. The research team has developed a prototype pothole management program. The program includes a mobile application and two machine learning models. The mobile app enables users to upload images of potholes, report relevant information, and provide driving directions to the pothole location. With the help of this application, the user can seamlessly capture images of the potholes, record pertinent information, and submit the data for necessary action. The mobile application is an essential tool in the Pot
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Forero Fuarez, Luis Carlos. Procesamiento de imágenes. Escuela Tecnológica Instituto Técnico Central - ETITC, 2023. http://dx.doi.org/10.55411/2023.4.

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El semillero tiene como uno de sus objetivos, la enseñanza y la aplicación de técnicas y herramientas de inteligencia artificial en áreas de la ingeniería electromecánica y afines. Para ello se seguirá un proceso que requerirá en sus primeras etapas la recopilación de la información, su limpieza, transformación y análisis, persiguiendo mediante el aprendizaje continuo de los estudiantes y su desarrollo en posteriores etapas, la implementación de modelos y/o arquitecturas que permitan desarrollar un modelo de IA basado en técnicas de visión por computadora y aprendizaje automático para reconoce
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