Artigos de revistas sobre o tema "Smoke and fire detection"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Veja os 50 melhores artigos de revistas para estudos sobre o assunto "Smoke and fire detection".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Veja os artigos de revistas das mais diversas áreas científicas e compile uma bibliografia correta.
Dong, Wen-Hui, Xue-Er Sheng, Shu Wang e Tian Deng. "Experimental Study on Particle Size Distribution Characteristics of Aerosol for Fire Detection". Applied Sciences 13, n.º 9 (30 de abril de 2023): 5592. http://dx.doi.org/10.3390/app13095592.
Texto completo da fonteLu, Xiaoman, Xiaoyang Zhang, Fangjun Li, Mark A. Cochrane e Pubu Ciren. "Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions". Remote Sensing 13, n.º 2 (8 de janeiro de 2021): 196. http://dx.doi.org/10.3390/rs13020196.
Texto completo da fonteLu, Xiaoman, Xiaoyang Zhang, Fangjun Li, Mark A. Cochrane e Pubu Ciren. "Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions". Remote Sensing 13, n.º 2 (8 de janeiro de 2021): 196. http://dx.doi.org/10.3390/rs13020196.
Texto completo da fontePeat, Bob. "Fire detection without smoke". Physics World 6, n.º 6 (junho de 1993): 23–25. http://dx.doi.org/10.1088/2058-7058/6/6/18.
Texto completo da fonteHuang, Jingwen, Jiashun Zhou, Huizhou Yang, Yunfei Liu e Han Liu. "A Small-Target Forest Fire Smoke Detection Model Based on Deformable Transformer for End-to-End Object Detection". Forests 14, n.º 1 (16 de janeiro de 2023): 162. http://dx.doi.org/10.3390/f14010162.
Texto completo da fonteSun, Bingjian, Pengle Cheng e Ying Huang. "Few-Shot Fine-Grained Forest Fire Smoke Recognition Based on Metric Learning". Sensors 22, n.º 21 (1 de novembro de 2022): 8383. http://dx.doi.org/10.3390/s22218383.
Texto completo da fonteBhamra, Jaspreet Kaur, Shreyas Anantha Ramaprasad, Siddhant Baldota, Shane Luna, Eugene Zen, Ravi Ramachandra, Harrison Kim et al. "Multimodal Wildland Fire Smoke Detection". Remote Sensing 15, n.º 11 (27 de maio de 2023): 2790. http://dx.doi.org/10.3390/rs15112790.
Texto completo da fonteBashambu, Dr Shallu, Anupam Gupta e Sarthak Khandelwal. "Real Time Fire and Smoke Detection System". International Journal for Research in Applied Science and Engineering Technology 11, n.º 6 (30 de junho de 2023): 2593–600. http://dx.doi.org/10.22214/ijraset.2023.54039.
Texto completo da fonteYang, Huanyu, Jun Wang e Jiacun Wang. "Efficient Detection of Forest Fire Smoke in UAV Aerial Imagery Based on an Improved Yolov5 Model and Transfer Learning". Remote Sensing 15, n.º 23 (27 de novembro de 2023): 5527. http://dx.doi.org/10.3390/rs15235527.
Texto completo da fonteZheng, Xin, Feng Chen, Liming Lou, Pengle Cheng e Ying Huang. "Real-Time Detection of Full-Scale Forest Fire Smoke Based on Deep Convolution Neural Network". Remote Sensing 14, n.º 3 (23 de janeiro de 2022): 536. http://dx.doi.org/10.3390/rs14030536.
Texto completo da fonteQian, Jingjing, Ji Lin, Di Bai, Renjie Xu e Haifeng Lin. "Omni-Dimensional Dynamic Convolution Meets Bottleneck Transformer: A Novel Improved High Accuracy Forest Fire Smoke Detection Model". Forests 14, n.º 4 (19 de abril de 2023): 838. http://dx.doi.org/10.3390/f14040838.
Texto completo da fontePan, Jin, Xiaoming Ou e Liang Xu. "A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN". Forests 12, n.º 6 (10 de junho de 2021): 768. http://dx.doi.org/10.3390/f12060768.
Texto completo da fonterajendra rao shinde, Rajshree, Shruti Sable, Kartik masalkar, Harshad Gaulker, Shailesh nardwar, Tejashri shinde e J. B. fulzale. "HOSPITAL EMERGENCY SECURITY SYSTEM". International Journal of Engineering Applied Sciences and Technology 7, n.º 1 (1 de maio de 2022): 264–67. http://dx.doi.org/10.33564/ijeast.2022.v07i01.038.
Texto completo da fonteHong, Ter-Ki, e 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, n.º 4 (31 de dezembro de 2022): 45–55. http://dx.doi.org/10.7731/kifse.96827602.
Texto completo da fonteNgoc, Pham Van Bach, Le Huy Hoang, Le Minh Hieu, Ngoc Hai Nguyen, Nguyen Luong Thien e Van Tuan Doan. "Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot". Engineering, Technology & Applied Science Research 13, n.º 5 (13 de outubro de 2023): 11843–49. http://dx.doi.org/10.48084/etasr.6252.
Texto completo da fonteGonçalves, Leon Augusto Okida, Rafik Ghali e Moulay A. Akhloufi. "YOLO-Based Models for Smoke and Wildfire Detection in Ground and Aerial Images". Fire 7, n.º 4 (14 de abril de 2024): 140. http://dx.doi.org/10.3390/fire7040140.
Texto completo da fonteTrinath Basu, M., Ragipati Karthik, J. Mahitha e V. Lokesh Reddy. "IoT based forest fire detection system". International Journal of Engineering & Technology 7, n.º 2.7 (18 de março de 2018): 124. http://dx.doi.org/10.14419/ijet.v7i2.7.10277.
Texto completo da fonteSawant, Swapnil, Samarth Kumbhar, Bhakti Chauhan, Gaurav Chaudhari e Prachi Thakkar. "Integrated Fire Detection System using ML and IOT". International Journal for Research in Applied Science and Engineering Technology 12, n.º 4 (30 de abril de 2024): 1738–41. http://dx.doi.org/10.22214/ijraset.2024.60063.
Texto completo da fonteSawant, Swapnil. "Integrated Fire Detection System using ML and IOT". International Journal for Research in Applied Science and Engineering Technology 12, n.º 5 (31 de maio de 2024): 2091–100. http://dx.doi.org/10.22214/ijraset.2024.61810.
Texto completo da fonteChetoui, Mohamed, e Moulay A. Akhloufi. "Fire and Smoke Detection Using Fine-Tuned YOLOv8 and YOLOv7 Deep Models". Fire 7, n.º 4 (12 de abril de 2024): 135. http://dx.doi.org/10.3390/fire7040135.
Texto completo da fonteVinay, Kumar Jain, e Jain Chitrangad. "Fire and smoke detection using YOLOv8". i-manager's Journal on Artificial Intelligence & Machine Learning 1, n.º 2 (2023): 22. http://dx.doi.org/10.26634/jaim.1.2.19849.
Texto completo da fonteAleshkov, M. V., S. V. Popov, N. G. Topolskiy, A. V. Mokshantsev, K. A. Mikhaylov, D. S. Afanasov, K. N. Samsonov e 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.
Texto completo da fonteYin, Hang, Yurong Wei, Hedan Liu, Shuangyin Liu, Chuanyun Liu e Yacui Gao. "Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection". Complexity 2020 (12 de novembro de 2020): 1–12. http://dx.doi.org/10.1155/2020/6843869.
Texto completo da fonteWu, Xuehui, Xiaobo Lu e Henry Leung. "A Video Based Fire Smoke Detection Using Robust AdaBoost". Sensors 18, n.º 11 (5 de novembro de 2018): 3780. http://dx.doi.org/10.3390/s18113780.
Texto completo da fonteHong, Ter-Ki, e 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, n.º 4 (19 de novembro de 2021): 85. http://dx.doi.org/10.3390/fire4040085.
Texto completo da fonteHossain, F. M. Anim, Youmin M. Zhang e 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, n.º 4 (1 de dezembro de 2020): 285–309. http://dx.doi.org/10.1139/juvs-2020-0009.
Texto completo da fonteDing, Yunhong, Mingyang Wang, Yujia Fu e 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, n.º 5 (10 de maio de 2024): 839. http://dx.doi.org/10.3390/f15050839.
Texto completo da fonteSun, Long, Yidan Li e Tongxin Hu. "ForestFireDetector: Expanding Channel Depth for Fine-Grained Feature Learning in Forest Fire Smoke Detection". Forests 14, n.º 11 (30 de outubro de 2023): 2157. http://dx.doi.org/10.3390/f14112157.
Texto completo da fonteSinha, Manya, Shivank Solanki, Sudeep Batra, Dr Yojna Arora e Abhishek Tewatia. "Fire Alarm System Through Smoke Detection". International Journal of Innovative Research in Computer Science and Technology 11, n.º 4 (1 de julho de 2023): 01–04. http://dx.doi.org/10.55524/ijircst.2023.11.4.1.
Texto completo da fonteKalmykov, Sergey Petrovich, e Viktor Nikolaevich Tokarev. "Influence of room height on estimated fire detection time". Technology of technosphere safety, n.º 100 (2023): 100–113. http://dx.doi.org/10.25257/tts.2023.2.100.100-113.
Texto completo da fonteZhao, Liang, Jixue Liu, Stefan Peters, Jiuyong Li, Simon Oliver e 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, n.º 13 (25 de junho de 2022): 3047. http://dx.doi.org/10.3390/rs14133047.
Texto completo da fonteChoi, Su-Gil, Yoo-Jeong Choi, Yeong-Jae Nam e 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, n.º 1 (28 de fevereiro de 2021): 48–57. http://dx.doi.org/10.7731/kifse.23b37311.
Texto completo da fonteHo, 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.
Texto completo da fonteYin, Hang, Mingxuan Chen, Wenting Fan, Yuxuan Jin, Shahbaz Gul Hassan e Shuangyin Liu. "Efficient Smoke Detection Based on YOLO v5s". Mathematics 10, n.º 19 (25 de setembro de 2022): 3493. http://dx.doi.org/10.3390/math10193493.
Texto completo da fonteSun, Baoshan, Kaiyu Bi e Qiuyan Wang. "YOLOv7-FIRE: A tiny-fire identification and detection method applied on UAV". AIMS Mathematics 9, n.º 5 (2024): 10775–801. http://dx.doi.org/10.3934/math.2024526.
Texto completo da fonteFeng, Xuhong, Pengle Cheng, Feng Chen e Ying Huang. "Full-Scale Fire Smoke Root Detection Based on Connected Particles". Sensors 22, n.º 18 (7 de setembro de 2022): 6748. http://dx.doi.org/10.3390/s22186748.
Texto completo da fonteXiong, Ding, e Lu Yan. "Early smoke detection of forest fires based on SVM image segmentation". Journal of Forest Science 65, No. 4 (26 de abril de 2019): 150–59. http://dx.doi.org/10.17221/82/2018-jfs.
Texto completo da fonteRoh, Joohyung, Yukyung Kim e Minsuk Kong. "Fire Image Classification Based on Convolutional Neural Network for Smart Fire Detection". International Journal of Fire Science and Engineering 36, n.º 3 (30 de setembro de 2022): 51–61. http://dx.doi.org/10.7731/kifse.cb750817.
Texto completo da fonteHan, Ziqi, Ye Tian, Change Zheng e Fengjun Zhao. "Forest Fire Smoke Detection Based on Multiple Color Spaces Deep Feature Fusion". Forests 15, n.º 4 (11 de abril de 2024): 689. http://dx.doi.org/10.3390/f15040689.
Texto completo da fonteBelure, Prasad, Chirag Bhagat, Om Bhadane, Girija Bendale, Shourya Bhade, Chetan Bhagat e Vaishali Saval. "Low Power Forest Fire Detection". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de maio de 2023): 2498–500. http://dx.doi.org/10.22214/ijraset.2023.51967.
Texto completo da fonteWang, Zewei, Change Zheng, Jiyan Yin, Ye Tian e Wenbin Cui. "A Semantic Segmentation Method for Early Forest Fire Smoke Based on Concentration Weighting". Electronics 10, n.º 21 (31 de outubro de 2021): 2675. http://dx.doi.org/10.3390/electronics10212675.
Texto completo da fonteUtkin, Andrei B., Armando Fernandes, Fernando Simões, Alexander Lavrov e Rui Vilar. "Feasibility of forest-fire smoke detection using lidar". International Journal of Wildland Fire 12, n.º 2 (2003): 159. http://dx.doi.org/10.1071/wf02048.
Texto completo da fonteLi, Tingting, Changchun Zhang, Haowei Zhu e Junguo Zhang. "Adversarial Fusion Network for Forest Fire Smoke Detection". Forests 13, n.º 3 (22 de fevereiro de 2022): 366. http://dx.doi.org/10.3390/f13030366.
Texto completo da fonteLee, Yeunghak, e 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, n.º 10 (15 de outubro de 2019): 1167. http://dx.doi.org/10.3390/electronics8101167.
Texto completo da fonteMikolai, Imrich, e Ján Tkáč. "Firefighting Systems and Video Smoke Detection as a Significant Part of Fire Safety in the Building". Advanced Materials Research 1057 (outubro de 2014): 196–203. http://dx.doi.org/10.4028/www.scientific.net/amr.1057.196.
Texto completo da fonteDeng, Li, Qian Chen, Yuanhua He, Xiubao Sui e Qin Wang. "Detection of smoke from infrared image frames in the aircraft cargoes". International Journal of Distributed Sensor Networks 17, n.º 4 (abril de 2021): 155014772110098. http://dx.doi.org/10.1177/15501477211009808.
Texto completo da fonteChen, Xin, Yipeng Xue, Qingshan Hou, Yan Fu e Yaolin Zhu. "RepVGG-YOLOv7: A Modified YOLOv7 for Fire Smoke Detection". Fire 6, n.º 10 (7 de outubro de 2023): 383. http://dx.doi.org/10.3390/fire6100383.
Texto completo da fonteWang, Aoran, Guanghao Liang, Xuan Wang e Yongchao Song. "Application of the YOLOv6 Combining CBAM and CIoU in Forest Fire and Smoke Detection". Forests 14, n.º 11 (17 de novembro de 2023): 2261. http://dx.doi.org/10.3390/f14112261.
Texto completo da fonteHamzah, Shipun Anuar, Mohd Noh Dalimin, Mohamad Md Som, Mohd Shamian Zainal, Khairun Nidzam Ramli, Wahyu Mulyo Utomo e 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, n.º 3 (1 de dezembro de 2022): 229. http://dx.doi.org/10.11591/ijict.v11i3.pp229-239.
Texto completo da fonteBi, Zhen Bo, e Hua Yang. "Fire Image Detection System Based on Cloud Workflow". Applied Mechanics and Materials 678 (outubro de 2014): 174–79. http://dx.doi.org/10.4028/www.scientific.net/amm.678.174.
Texto completo da fonte