Artículos de revistas sobre el tema "U-NET CNN"
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Sariturk, Batuhan y Dursun Zafer Seker. "A Residual-Inception U-Net (RIU-Net) Approach and Comparisons with U-Shaped CNN and Transformer Models for Building Segmentation from High-Resolution Satellite Images". Sensors 22, n.º 19 (8 de octubre de 2022): 7624. http://dx.doi.org/10.3390/s22197624.
Texto completoChoi, Keong-Hun y Jong-Eun Ha. "Edge Detection based-on U-Net using Edge Classification CNN". Journal of Institute of Control, Robotics and Systems 25, n.º 8 (31 de agosto de 2019): 684–89. http://dx.doi.org/10.5302/j.icros.2019.19.0119.
Texto completoDi Benedetto, Alessandro, Margherita Fiani y Lucas Matias Gujski. "U-Net-Based CNN Architecture for Road Crack Segmentation". Infrastructures 8, n.º 5 (6 de mayo de 2023): 90. http://dx.doi.org/10.3390/infrastructures8050090.
Texto completoDjohar, Muhammad Awaludin, Anita Desiani, Dewi Lestari Dwi Putri, Des Alwine Zayanti, Ali Amran, Irmeilyana Irmeilyana y Novi Rustiana Dewi. "Segmentasi Citra Hati Menggunakan Metode Convolutional Neural Network dengan Arsitektur U-Net". JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING 6, n.º 1 (23 de julio de 2022): 221–34. http://dx.doi.org/10.31289/jite.v6i1.6751.
Texto completoMiron, Casian, Laura Ioana Grigoras, Radu Ciucu y Vasile Manta. "Eye Image Segmentation Method Based on the Modified U-Net CNN Architecture". Bulletin of the Polytechnic Institute of Iași. Electrical Engineering, Power Engineering, Electronics Section 67, n.º 2 (1 de junio de 2021): 41–52. http://dx.doi.org/10.2478/bipie-2021-0010.
Texto completoSariturk, Batuhan, Damla Kumbasar y Dursun Zafer Seker. "Comparative Analysis of Different CNN Models for Building Segmentation from Satellite and UAV Images". Photogrammetric Engineering & Remote Sensing 89, n.º 2 (1 de febrero de 2023): 97–105. http://dx.doi.org/10.14358/pers.22-00084r2.
Texto completoErdem, Firat, Nuri Erkin Ocer, Dilek Kucuk Matci, Gordana Kaplan y Ugur Avdan. "Apricot Tree Detection from UAV-Images Using Mask R-CNN and U-Net". Photogrammetric Engineering & Remote Sensing 89, n.º 2 (1 de febrero de 2023): 89–96. http://dx.doi.org/10.14358/pers.22-00086r2.
Texto completoK.Narasimha Rao, Kesani Prudhvidhar Reddy, Gopavarapu Sai Satya Sreekar y Gade Gopinath Reddy. "Retinal blood vessels segmentation using CNN algorithm". international journal of engineering technology and management sciences 7, n.º 3 (2023): 499–504. http://dx.doi.org/10.46647/ijetms.2023.v07i03.70.
Texto completoLutsenko, V. S. y A. E. Shukhman. "SEGMENTATION OF MEDICAL IMAGES BY CONVOLUTIONAL NEURAL NETWORKS". Vestnik komp'iuternykh i informatsionnykh tekhnologii, n.º 216 (junio de 2022): 40–50. http://dx.doi.org/10.14489/vkit.2022.06.pp.040-050.
Texto completoYounisse, Remah, Rawan Ghnemat y Jaafer Al Saraireh. "Fine-tuning U-net for medical image segmentation based on activation function, optimizer and pooling layer". International Journal of Electrical and Computer Engineering (IJECE) 13, n.º 5 (1 de octubre de 2023): 5406. http://dx.doi.org/10.11591/ijece.v13i5.pp5406-5417.
Texto completoMukkapati, Naveen y M. S. Anbarasi. "Brain Tumor Classification Based on Enhanced CNN Model". Revue d'Intelligence Artificielle 36, n.º 1 (28 de febrero de 2022): 125–30. http://dx.doi.org/10.18280/ria.360114.
Texto completoOhura, Norihiko, Ryota Mitsuno, Masanobu Sakisaka, Yuta Terabe, Yuki Morishige, Atsushi Uchiyama, Takumi Okoshi, Iizaka Shinji y Akihiko Takushima. "Convolutional neural networks for wound detection: the role of artificial intelligence in wound care". Journal of Wound Care 28, Sup10 (1 de octubre de 2019): S13—S24. http://dx.doi.org/10.12968/jowc.2019.28.sup10.s13.
Texto completoTong, Xiaozhong, Bei Sun, Junyu Wei, Zhen Zuo y Shaojing Su. "EAAU-Net: Enhanced Asymmetric Attention U-Net for Infrared Small Target Detection". Remote Sensing 13, n.º 16 (12 de agosto de 2021): 3200. http://dx.doi.org/10.3390/rs13163200.
Texto completoLiu, Ziqian, Wenbing Wang, Qing Ma, Xianming Liu y Junjun Jiang. "Rethinking 3D-CNN in Hyperspectral Image Super-Resolution". Remote Sensing 15, n.º 10 (15 de mayo de 2023): 2574. http://dx.doi.org/10.3390/rs15102574.
Texto completoJwaid, Wasan M., Zainab Shaker Matar Al-Husseini y Ahmad H. Sabry. "Development of brain tumor segmentation of magnetic resonance imaging (MRI) using U-Net deep learning". Eastern-European Journal of Enterprise Technologies 4, n.º 9(112) (31 de agosto de 2021): 23–31. http://dx.doi.org/10.15587/1729-4061.2021.238957.
Texto completoKonovalenko, Ihor, Pavlo Maruschak, Janette Brezinová, Olegas Prentkovskis y Jakub Brezina. "Research of U-Net-Based CNN Architectures for Metal Surface Defect Detection". Machines 10, n.º 5 (29 de abril de 2022): 327. http://dx.doi.org/10.3390/machines10050327.
Texto completoTemenos, Anastasios, Nikos Temenos, Anastasios Doulamis y Nikolaos Doulamis. "On the Exploration of Automatic Building Extraction from RGB Satellite Images Using Deep Learning Architectures Based on U-Net". Technologies 10, n.º 1 (29 de enero de 2022): 19. http://dx.doi.org/10.3390/technologies10010019.
Texto completoFathipoor, H., R. Shah-Hosseini y H. Arefi. "CROP AND WEED SEGMENTATION ON GROUND-BASED IMAGES USING DEEP CONVOLUTIONAL NEURAL NETWORK". ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W1-2022 (13 de enero de 2023): 195–200. http://dx.doi.org/10.5194/isprs-annals-x-4-w1-2022-195-2023.
Texto completoWang, An, Ren Togo, Takahiro Ogawa y Miki Haseyama. "Defect Detection of Subway Tunnels Using Advanced U-Net Network". Sensors 22, n.º 6 (17 de marzo de 2022): 2330. http://dx.doi.org/10.3390/s22062330.
Texto completoMeng, Yongan, Hailei Lan, Yuqian Hu, Zailiang Chen, Pingbo Ouyang y Jing Luo. "Application of Improved U-Net Convolutional Neural Network for Automatic Quantification of the Foveal Avascular Zone in Diabetic Macular Ischemia". Journal of Diabetes Research 2022 (26 de febrero de 2022): 1–8. http://dx.doi.org/10.1155/2022/4612554.
Texto completoGunawan, Rudy, Yvonne Tran, Jinchuan Zheng, Hung Nguyen y Rifai Chai. "Image Recovery from Synthetic Noise Artifacts in CT Scans Using Modified U-Net". Sensors 22, n.º 18 (16 de septiembre de 2022): 7031. http://dx.doi.org/10.3390/s22187031.
Texto completoМ. Ж. Қалдарова, А. С. Аканова y Н. М. Кашкимбаева. "АУЫЛШАРУАШЫЛЫҚ ЖЕРЛЕРІНІҢ ЕГІС АЛҚАПТАРЫН СЕГМЕНТТЕУДЕ НЕЙРОНДЫҚ ЖЕЛІНІҢ U-NET АРХИТЕКТУРАСЫНЫҢ ҚОЛДАНЫЛУЫ". Bulletin of Toraighyrov University. Energetics series, n.º 4.2022 (30 de diciembre de 2022): 198–211. http://dx.doi.org/10.48081/kysd9304.
Texto completoHoffman, Jay P., Timothy F. Rahmes, Anthony J. Wimmers y Wayne F. Feltz. "The Application of a Convolutional Neural Network for the Detection of Contrails in Satellite Imagery". Remote Sensing 15, n.º 11 (31 de mayo de 2023): 2854. http://dx.doi.org/10.3390/rs15112854.
Texto completoViedma, Ignacio A., David Alonso-Caneiro, Scott A. Read y Michael J. Collins. "OCT Retinal and Choroidal Layer Instance Segmentation Using Mask R-CNN". Sensors 22, n.º 5 (4 de marzo de 2022): 2016. http://dx.doi.org/10.3390/s22052016.
Texto completoChan, Huang-Tian y Chi-Ching Chang. "Decryption of Deterministic Phase-Encoded Digital Holography Using Convolutional Neural Networks". Photonics 10, n.º 6 (25 de mayo de 2023): 612. http://dx.doi.org/10.3390/photonics10060612.
Texto completoGhulam, Rehana, Sammar Fatima, Tariq Ali, Nazir Ahmad Zafar, Abdullah A. Asiri, Hassan A. Alshamrani, Samar M. Alqhtani y Khlood M. Mehdar. "A U-Net-Based CNN Model for Detection and Segmentation of Brain Tumor". Computers, Materials & Continua 74, n.º 1 (2023): 1333–49. http://dx.doi.org/10.32604/cmc.2023.031695.
Texto completoChen, Dong, Fan Hu, P. Takis Mathiopoulos, Zhenxin Zhang y Jiju Peethambaran. "MC-UNet: Martian Crater Segmentation at Semantic and Instance Levels Using U-Net-Based Convolutional Neural Network". Remote Sensing 15, n.º 1 (2 de enero de 2023): 266. http://dx.doi.org/10.3390/rs15010266.
Texto completoUrase, Yasuyo, Mizuho Nishio, Yoshiko Ueno, Atsushi K. Kono, Keitaro Sofue, Tomonori Kanda, Takaki Maeda, Munenobu Nogami, Masatoshi Hori y Takamichi Murakami. "Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis". Applied Sciences 10, n.º 13 (28 de junio de 2020): 4446. http://dx.doi.org/10.3390/app10134446.
Texto completoZhou, Zhengyin, Zhihui Fu, Juncheng Jia y Jun Lv. "Rib Fracture Detection with Dual-Attention Enhanced U-Net". Computational and Mathematical Methods in Medicine 2022 (18 de agosto de 2022): 1–13. http://dx.doi.org/10.1155/2022/8945423.
Texto completoHuang, Tinglong, Xuelan Zheng, Lisui He y Zhiliang Chen. "Diagnostic Value of Deep Learning-Based CT Feature for Severe Pulmonary Infection". Journal of Healthcare Engineering 2021 (26 de noviembre de 2021): 1–11. http://dx.doi.org/10.1155/2021/5359084.
Texto completoChen, Panpan, Chengcheng Liu, Ting Feng, Yong Li y Dean Ta. "Improved Photoacoustic Imaging of Numerical Bone Model Based on Attention Block U-Net Deep Learning Network". Applied Sciences 10, n.º 22 (15 de noviembre de 2020): 8089. http://dx.doi.org/10.3390/app10228089.
Texto completoXu, Cong, Changqing Yu y Shanwen Zhang. "Lightweight Multi-Scale Dilated U-Net for Crop Disease Leaf Image Segmentation". Electronics 11, n.º 23 (29 de noviembre de 2022): 3947. http://dx.doi.org/10.3390/electronics11233947.
Texto completoZhang, Jiawei, Xin Zhao, Tao Jiang, Md Mamunur Rahaman, Yudong Yao, Yu-Hao Lin, Jinghua Zhang, Ao Pan, Marcin Grzegorzek y Chen Li. "An Application of Pixel Interval Down-Sampling (PID) for Dense Tiny Microorganism Counting on Environmental Microorganism Images". Applied Sciences 12, n.º 14 (21 de julio de 2022): 7314. http://dx.doi.org/10.3390/app12147314.
Texto completoAsiri, Abdullah A., Ahmad Shaf, Tariq Ali, Muhammad Aamir, Muhammad Irfan, Saeed Alqahtani, Khlood M. Mehdar et al. "Brain Tumor Detection and Classification Using Fine-Tuned CNN with ResNet50 and U-Net Model: A Study on TCGA-LGG and TCIA Dataset for MRI Applications". Life 13, n.º 7 (26 de junio de 2023): 1449. http://dx.doi.org/10.3390/life13071449.
Texto completoTaher, Fatma y Neema Prakash. "Automatic cerebrovascular segmentation methods-a review". IAES International Journal of Artificial Intelligence (IJ-AI) 10, n.º 3 (1 de septiembre de 2021): 576. http://dx.doi.org/10.11591/ijai.v10.i3.pp576-583.
Texto completoAffane, Abir, Adrian Kucharski, Paul Chapuis, Samuel Freydier, Marie-Ange Lebre, Antoine Vacavant y Anna Fabijańska. "Segmentation of Liver Anatomy by Combining 3D U-Net Approaches". Applied Sciences 11, n.º 11 (26 de mayo de 2021): 4895. http://dx.doi.org/10.3390/app11114895.
Texto completoDu, Getao, Xu Cao, Jimin Liang, Xueli Chen y Yonghua Zhan. "Medical Image Segmentation based on U-Net: A Review". Journal of Imaging Science and Technology 64, n.º 2 (1 de marzo de 2020): 20508–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2020.64.2.020508.
Texto completoAdoui, Mahmoudi, Larhmam y Benjelloun. "MRI Breast Tumor Segmentation Using Different Encoder and Decoder CNN Architectures". Computers 8, n.º 3 (29 de junio de 2019): 52. http://dx.doi.org/10.3390/computers8030052.
Texto completoEl Asri, Smail Ait, Samir El Adib, Ismail Negabi y Naoufal Raissouni. "A Modular System Based on U-Net for Automatic Building Extraction from very high-resolution satellite images". E3S Web of Conferences 351 (2022): 01071. http://dx.doi.org/10.1051/e3sconf/202235101071.
Texto completoBanu, Syeda Furruka, Md Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Domenec Puig y Hatem A. Raswan. "AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation". Applied Sciences 11, n.º 21 (28 de octubre de 2021): 10132. http://dx.doi.org/10.3390/app112110132.
Texto completoNasser, Soraya, Moulkheir Naoui, Ghalem Belalem y Saïd Mahmoudi. "Semantic Segmentation of Hippocampal Subregions With U-Net Architecture". International Journal of E-Health and Medical Communications 12, n.º 6 (noviembre de 2021): 1–20. http://dx.doi.org/10.4018/ijehmc.20211101.oa4.
Texto completoFeiger, Bradley, Erick Lorenzana-Saldivar, Colin Cooke, Roarke Horstmeyer, Muath Bishawi, Julie Doberne, G. Chad Hughes, David Ranney, Soraya Voigt y Amanda Randles. "Evaluation of U-Net Based Architectures for Automatic Aortic Dissection Segmentation". ACM Transactions on Computing for Healthcare 3, n.º 1 (31 de enero de 2022): 1–16. http://dx.doi.org/10.1145/3472302.
Texto completoLee, Su Hyun, JiHwan Lee, Kyung-Soo Oh, Jong Pil Yoon, Anna Seo, YoungJin Jeong y Seok Won Chung. "Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm". PLOS ONE 18, n.º 5 (18 de mayo de 2023): e0284111. http://dx.doi.org/10.1371/journal.pone.0284111.
Texto completoQuenum, Jerome, Iryna V. Zenyuk y Daniela Ushizima. "Lithium Metal Battery Quality Control via Transformer–CNN Segmentation". Journal of Imaging 9, n.º 6 (31 de mayo de 2023): 111. http://dx.doi.org/10.3390/jimaging9060111.
Texto completoShah. Md. Nazmul Arefin, Abu Shahed, Shah Mohd. Ishtiaque Ahammed Khan Ishti, Mst Marium Akter y Nusrat Jahan. "Deep learning approach for detecting and localizing brain tumor from magnetic resonance imaging images". Indonesian Journal of Electrical Engineering and Computer Science 29, n.º 3 (1 de marzo de 2023): 1729. http://dx.doi.org/10.11591/ijeecs.v29.i3.pp1729-1737.
Texto completoRan, Si, Jianli Ding, Bohua Liu, Xiangyu Ge y Guolin Ma. "Multi-U-Net: Residual Module under Multisensory Field and Attention Mechanism Based Optimized U-Net for VHR Image Semantic Segmentation". Sensors 21, n.º 5 (5 de marzo de 2021): 1794. http://dx.doi.org/10.3390/s21051794.
Texto completoYeung, Michael, Evis Sala, Carola-Bibiane Schönlieb y Leonardo Rundo. "Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy". Computers in Biology and Medicine 137 (octubre de 2021): 104815. http://dx.doi.org/10.1016/j.compbiomed.2021.104815.
Texto completoBezmaternykh, P. V., D. A. Ilin y D. P. Nikolaev. "U-Net-bin: hacking the document image binarization contest". Computer Optics 43, n.º 5 (octubre de 2019): 825–32. http://dx.doi.org/10.18287/2412-6179-2019-43-5-825-832.
Texto completoPang, Shuyang, Xuewen Xiao, Yuao Cui, Shangwei Mao, Xin Cao, Hongsheng Jia, Hao Wang, Fenghua Tong y Xiaohui Zhang. "GCN-Unet: A Computer Vision Method with Application to Industrial Granularity Segmentation". Mobile Information Systems 2022 (25 de agosto de 2022): 1–9. http://dx.doi.org/10.1155/2022/1466261.
Texto completoBayrakdar, Ibrahim S., Kaan Orhan, Özer Çelik, Elif Bilgir, Hande Sağlam, Fatma Akkoca Kaplan, Sinem Atay Görür, Alper Odabaş, Ahmet Faruk Aslan y Ingrid Różyło-Kalinowska. "A U-Net Approach to Apical Lesion Segmentation on Panoramic Radiographs". BioMed Research International 2022 (15 de enero de 2022): 1–7. http://dx.doi.org/10.1155/2022/7035367.
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