Artykuły w czasopismach na temat „Smoke and fire detection”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Sprawdź 50 najlepszych artykułów w czasopismach naukowych na temat „Smoke and fire detection”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.
Dong, Wen-Hui, Xue-Er Sheng, Shu Wang i Tian Deng. "Experimental Study on Particle Size Distribution Characteristics of Aerosol for Fire Detection". Applied Sciences 13, nr 9 (30.04.2023): 5592. http://dx.doi.org/10.3390/app13095592.
Pełny tekst źródłaLu, Xiaoman, Xiaoyang Zhang, Fangjun Li, Mark A. Cochrane i Pubu Ciren. "Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions". Remote Sensing 13, nr 2 (8.01.2021): 196. http://dx.doi.org/10.3390/rs13020196.
Pełny tekst źródłaLu, Xiaoman, Xiaoyang Zhang, Fangjun Li, Mark A. Cochrane i Pubu Ciren. "Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions". Remote Sensing 13, nr 2 (8.01.2021): 196. http://dx.doi.org/10.3390/rs13020196.
Pełny tekst źródłaPeat, Bob. "Fire detection without smoke". Physics World 6, nr 6 (czerwiec 1993): 23–25. http://dx.doi.org/10.1088/2058-7058/6/6/18.
Pełny tekst źródłaHuang, Jingwen, Jiashun Zhou, Huizhou Yang, Yunfei Liu i Han Liu. "A Small-Target Forest Fire Smoke Detection Model Based on Deformable Transformer for End-to-End Object Detection". Forests 14, nr 1 (16.01.2023): 162. http://dx.doi.org/10.3390/f14010162.
Pełny tekst źródłaSun, Bingjian, Pengle Cheng i Ying Huang. "Few-Shot Fine-Grained Forest Fire Smoke Recognition Based on Metric Learning". Sensors 22, nr 21 (1.11.2022): 8383. http://dx.doi.org/10.3390/s22218383.
Pełny tekst źródłaBhamra, Jaspreet Kaur, Shreyas Anantha Ramaprasad, Siddhant Baldota, Shane Luna, Eugene Zen, Ravi Ramachandra, Harrison Kim i in. "Multimodal Wildland Fire Smoke Detection". Remote Sensing 15, nr 11 (27.05.2023): 2790. http://dx.doi.org/10.3390/rs15112790.
Pełny tekst źródłaBashambu, Dr Shallu, Anupam Gupta i Sarthak Khandelwal. "Real Time Fire and Smoke Detection System". International Journal for Research in Applied Science and Engineering Technology 11, nr 6 (30.06.2023): 2593–600. http://dx.doi.org/10.22214/ijraset.2023.54039.
Pełny tekst źródłaYang, Huanyu, Jun Wang i Jiacun Wang. "Efficient Detection of Forest Fire Smoke in UAV Aerial Imagery Based on an Improved Yolov5 Model and Transfer Learning". Remote Sensing 15, nr 23 (27.11.2023): 5527. http://dx.doi.org/10.3390/rs15235527.
Pełny tekst źródłaZheng, Xin, Feng Chen, Liming Lou, Pengle Cheng i Ying Huang. "Real-Time Detection of Full-Scale Forest Fire Smoke Based on Deep Convolution Neural Network". Remote Sensing 14, nr 3 (23.01.2022): 536. http://dx.doi.org/10.3390/rs14030536.
Pełny tekst źródłaQian, Jingjing, Ji Lin, Di Bai, Renjie Xu i Haifeng Lin. "Omni-Dimensional Dynamic Convolution Meets Bottleneck Transformer: A Novel Improved High Accuracy Forest Fire Smoke Detection Model". Forests 14, nr 4 (19.04.2023): 838. http://dx.doi.org/10.3390/f14040838.
Pełny tekst źródłaPan, Jin, Xiaoming Ou i Liang Xu. "A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN". Forests 12, nr 6 (10.06.2021): 768. http://dx.doi.org/10.3390/f12060768.
Pełny tekst źródłarajendra rao shinde, Rajshree, Shruti Sable, Kartik masalkar, Harshad Gaulker, Shailesh nardwar, Tejashri shinde i J. B. fulzale. "HOSPITAL EMERGENCY SECURITY SYSTEM". International Journal of Engineering Applied Sciences and Technology 7, nr 1 (1.05.2022): 264–67. http://dx.doi.org/10.33564/ijeast.2022.v07i01.038.
Pełny tekst źródłaHong, Ter-Ki, i Seul-Hyun Park. "Effects of Optical Properties of Smoke Particles on Fire Detection Characteristics predicted by a Fire Dynamic Simulator Model". International Journal of Fire Science and Engineering 36, nr 4 (31.12.2022): 45–55. http://dx.doi.org/10.7731/kifse.96827602.
Pełny tekst źródłaNgoc, Pham Van Bach, Le Huy Hoang, Le Minh Hieu, Ngoc Hai Nguyen, Nguyen Luong Thien i Van Tuan Doan. "Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot". Engineering, Technology & Applied Science Research 13, nr 5 (13.10.2023): 11843–49. http://dx.doi.org/10.48084/etasr.6252.
Pełny tekst źródłaGonçalves, Leon Augusto Okida, Rafik Ghali i Moulay A. Akhloufi. "YOLO-Based Models for Smoke and Wildfire Detection in Ground and Aerial Images". Fire 7, nr 4 (14.04.2024): 140. http://dx.doi.org/10.3390/fire7040140.
Pełny tekst źródłaTrinath Basu, M., Ragipati Karthik, J. Mahitha i V. Lokesh Reddy. "IoT based forest fire detection system". International Journal of Engineering & Technology 7, nr 2.7 (18.03.2018): 124. http://dx.doi.org/10.14419/ijet.v7i2.7.10277.
Pełny tekst źródłaSawant, Swapnil, Samarth Kumbhar, Bhakti Chauhan, Gaurav Chaudhari i Prachi Thakkar. "Integrated Fire Detection System using ML and IOT". International Journal for Research in Applied Science and Engineering Technology 12, nr 4 (30.04.2024): 1738–41. http://dx.doi.org/10.22214/ijraset.2024.60063.
Pełny tekst źródłaSawant, Swapnil. "Integrated Fire Detection System using ML and IOT". International Journal for Research in Applied Science and Engineering Technology 12, nr 5 (31.05.2024): 2091–100. http://dx.doi.org/10.22214/ijraset.2024.61810.
Pełny tekst źródłaChetoui, Mohamed, i Moulay A. Akhloufi. "Fire and Smoke Detection Using Fine-Tuned YOLOv8 and YOLOv7 Deep Models". Fire 7, nr 4 (12.04.2024): 135. http://dx.doi.org/10.3390/fire7040135.
Pełny tekst źródłaVinay, Kumar Jain, i Jain Chitrangad. "Fire and smoke detection using YOLOv8". i-manager's Journal on Artificial Intelligence & Machine Learning 1, nr 2 (2023): 22. http://dx.doi.org/10.26634/jaim.1.2.19849.
Pełny tekst źródłaAleshkov, M. V., S. V. Popov, N. G. Topolskiy, A. V. Mokshantsev, K. A. Mikhaylov, D. S. Afanasov, K. N. Samsonov i L. A. Iftodi. "Results of tests for the detection of a fire source using infrared measuring instruments". Technology of technosphere safety 93 (2021): 19–28. http://dx.doi.org/10.25257/tts.2021.3.93.19-28.
Pełny tekst źródłaYin, Hang, Yurong Wei, Hedan Liu, Shuangyin Liu, Chuanyun Liu i Yacui Gao. "Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection". Complexity 2020 (12.11.2020): 1–12. http://dx.doi.org/10.1155/2020/6843869.
Pełny tekst źródłaWu, Xuehui, Xiaobo Lu i Henry Leung. "A Video Based Fire Smoke Detection Using Robust AdaBoost". Sensors 18, nr 11 (5.11.2018): 3780. http://dx.doi.org/10.3390/s18113780.
Pełny tekst źródłaHong, Ter-Ki, i Seul-Hyun Park. "Numerical Analysis of Smoke Behavior and Detection of Solid Combustible Fire Developed in Manned Exploration Module Based on Exploration Gravity". Fire 4, nr 4 (19.11.2021): 85. http://dx.doi.org/10.3390/fire4040085.
Pełny tekst źródłaHossain, F. M. Anim, Youmin M. Zhang i Masuda Akter Tonima. "Forest fire flame and smoke detection from UAV-captured images using fire-specific color features and multi-color space local binary pattern". Journal of Unmanned Vehicle Systems 8, nr 4 (1.12.2020): 285–309. http://dx.doi.org/10.1139/juvs-2020-0009.
Pełny tekst źródłaDing, Yunhong, Mingyang Wang, Yujia Fu i Qian Wang. "Forest Smoke-Fire Net (FSF Net): A Wildfire Smoke Detection Model That Combines MODIS Remote Sensing Images with Regional Dynamic Brightness Temperature Thresholds". Forests 15, nr 5 (10.05.2024): 839. http://dx.doi.org/10.3390/f15050839.
Pełny tekst źródłaSun, Long, Yidan Li i Tongxin Hu. "ForestFireDetector: Expanding Channel Depth for Fine-Grained Feature Learning in Forest Fire Smoke Detection". Forests 14, nr 11 (30.10.2023): 2157. http://dx.doi.org/10.3390/f14112157.
Pełny tekst źródłaSinha, Manya, Shivank Solanki, Sudeep Batra, Dr Yojna Arora i Abhishek Tewatia. "Fire Alarm System Through Smoke Detection". International Journal of Innovative Research in Computer Science and Technology 11, nr 4 (1.07.2023): 01–04. http://dx.doi.org/10.55524/ijircst.2023.11.4.1.
Pełny tekst źródłaKalmykov, Sergey Petrovich, i Viktor Nikolaevich Tokarev. "Influence of room height on estimated fire detection time". Technology of technosphere safety, nr 100 (2023): 100–113. http://dx.doi.org/10.25257/tts.2023.2.100.100-113.
Pełny tekst źródłaZhao, Liang, Jixue Liu, Stefan Peters, Jiuyong Li, Simon Oliver i Norman Mueller. "Investigating the Impact of Using IR Bands on Early Fire Smoke Detection from Landsat Imagery with a Lightweight CNN Model". Remote Sensing 14, nr 13 (25.06.2022): 3047. http://dx.doi.org/10.3390/rs14133047.
Pełny tekst źródłaChoi, Su-Gil, Yoo-Jeong Choi, Yeong-Jae Nam i Si-Kuk Kim. "Fire Detection Tendency through Combustion Products Generated during UL 268 Wood Flame Fire and Smoldering Fire Test". Fire Science and Engineering 35, nr 1 (28.02.2021): 48–57. http://dx.doi.org/10.7731/kifse.23b37311.
Pełny tekst źródłaHo, Chao-Ching. "Nighttime Fire/Smoke Detection System Based on a Support Vector Machine". Mathematical Problems in Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/428545.
Pełny tekst źródłaYin, Hang, Mingxuan Chen, Wenting Fan, Yuxuan Jin, Shahbaz Gul Hassan i Shuangyin Liu. "Efficient Smoke Detection Based on YOLO v5s". Mathematics 10, nr 19 (25.09.2022): 3493. http://dx.doi.org/10.3390/math10193493.
Pełny tekst źródłaSun, Baoshan, Kaiyu Bi i Qiuyan Wang. "YOLOv7-FIRE: A tiny-fire identification and detection method applied on UAV". AIMS Mathematics 9, nr 5 (2024): 10775–801. http://dx.doi.org/10.3934/math.2024526.
Pełny tekst źródłaFeng, Xuhong, Pengle Cheng, Feng Chen i Ying Huang. "Full-Scale Fire Smoke Root Detection Based on Connected Particles". Sensors 22, nr 18 (7.09.2022): 6748. http://dx.doi.org/10.3390/s22186748.
Pełny tekst źródłaXiong, Ding, i Lu Yan. "Early smoke detection of forest fires based on SVM image segmentation". Journal of Forest Science 65, No. 4 (26.04.2019): 150–59. http://dx.doi.org/10.17221/82/2018-jfs.
Pełny tekst źródłaRoh, Joohyung, Yukyung Kim i Minsuk Kong. "Fire Image Classification Based on Convolutional Neural Network for Smart Fire Detection". International Journal of Fire Science and Engineering 36, nr 3 (30.09.2022): 51–61. http://dx.doi.org/10.7731/kifse.cb750817.
Pełny tekst źródłaHan, Ziqi, Ye Tian, Change Zheng i Fengjun Zhao. "Forest Fire Smoke Detection Based on Multiple Color Spaces Deep Feature Fusion". Forests 15, nr 4 (11.04.2024): 689. http://dx.doi.org/10.3390/f15040689.
Pełny tekst źródłaBelure, Prasad, Chirag Bhagat, Om Bhadane, Girija Bendale, Shourya Bhade, Chetan Bhagat i Vaishali Saval. "Low Power Forest Fire Detection". International Journal for Research in Applied Science and Engineering Technology 11, nr 5 (31.05.2023): 2498–500. http://dx.doi.org/10.22214/ijraset.2023.51967.
Pełny tekst źródłaWang, Zewei, Change Zheng, Jiyan Yin, Ye Tian i Wenbin Cui. "A Semantic Segmentation Method for Early Forest Fire Smoke Based on Concentration Weighting". Electronics 10, nr 21 (31.10.2021): 2675. http://dx.doi.org/10.3390/electronics10212675.
Pełny tekst źródłaUtkin, Andrei B., Armando Fernandes, Fernando Simões, Alexander Lavrov i Rui Vilar. "Feasibility of forest-fire smoke detection using lidar". International Journal of Wildland Fire 12, nr 2 (2003): 159. http://dx.doi.org/10.1071/wf02048.
Pełny tekst źródłaLi, Tingting, Changchun Zhang, Haowei Zhu i Junguo Zhang. "Adversarial Fusion Network for Forest Fire Smoke Detection". Forests 13, nr 3 (22.02.2022): 366. http://dx.doi.org/10.3390/f13030366.
Pełny tekst źródłaLee, Yeunghak, i Jaechang Shim. "False Positive Decremented Research for Fire and Smoke Detection in Surveillance Camera using Spatial and Temporal Features Based on Deep Learning". Electronics 8, nr 10 (15.10.2019): 1167. http://dx.doi.org/10.3390/electronics8101167.
Pełny tekst źródłaMikolai, Imrich, i Ján Tkáč. "Firefighting Systems and Video Smoke Detection as a Significant Part of Fire Safety in the Building". Advanced Materials Research 1057 (październik 2014): 196–203. http://dx.doi.org/10.4028/www.scientific.net/amr.1057.196.
Pełny tekst źródłaDeng, Li, Qian Chen, Yuanhua He, Xiubao Sui i Qin Wang. "Detection of smoke from infrared image frames in the aircraft cargoes". International Journal of Distributed Sensor Networks 17, nr 4 (kwiecień 2021): 155014772110098. http://dx.doi.org/10.1177/15501477211009808.
Pełny tekst źródłaChen, Xin, Yipeng Xue, Qingshan Hou, Yan Fu i Yaolin Zhu. "RepVGG-YOLOv7: A Modified YOLOv7 for Fire Smoke Detection". Fire 6, nr 10 (7.10.2023): 383. http://dx.doi.org/10.3390/fire6100383.
Pełny tekst źródłaWang, Aoran, Guanghao Liang, Xuan Wang i Yongchao Song. "Application of the YOLOv6 Combining CBAM and CIoU in Forest Fire and Smoke Detection". Forests 14, nr 11 (17.11.2023): 2261. http://dx.doi.org/10.3390/f14112261.
Pełny tekst źródłaHamzah, Shipun Anuar, Mohd Noh Dalimin, Mohamad Md Som, Mohd Shamian Zainal, Khairun Nidzam Ramli, Wahyu Mulyo Utomo i Nor Azizi Yusoff. "High accuracy sensor nodes for a peat swamp forest fire detection using ESP32 camera". International Journal of Informatics and Communication Technology (IJ-ICT) 11, nr 3 (1.12.2022): 229. http://dx.doi.org/10.11591/ijict.v11i3.pp229-239.
Pełny tekst źródłaBi, Zhen Bo, i Hua Yang. "Fire Image Detection System Based on Cloud Workflow". Applied Mechanics and Materials 678 (październik 2014): 174–79. http://dx.doi.org/10.4028/www.scientific.net/amm.678.174.
Pełny tekst źródła