Optimized cross-module attention network and medium-scale dataset for effective fire detection

Zulfiqar Ahmad Khan; Fath U Min Ullah; Hikmat Yar; Waseem Ullah; Noman Khan; Min Je Kim; Sung Wook Baik

doi:10.1016/j.patcog.2024.111273

journal article May 01, 2025

Optimized cross-module attention network and medium-scale dataset for effective fire detection

Zulfiqar Ahmad Khan

Fath U Min Ullah

Hikmat Yar Waseem Ullah

Noman Khan Min Je Kim Sung Wook Baik

Pattern Recognition Vol. 161 pp. 111273 · Elsevier BV

View at Publisher Save 10.1016/j.patcog.2024.111273

Topics

No keywords indexed for this article. Browse by subject →

References

40

[1]

Li "An efficient fire detection method based on multiscale feature extraction, implicit deep supervision and channel attention mechanism" IEEE Trans. Image Process.. (2020) 10.1109/tip.2020.3016431

[2]

Yuan "A newton interpolation network for smoke semantic segmentation" Pattern Recognit. (2024)

[3]

Optimized Dual Fire Attention Network and Medium-Scale Fire Classification Benchmark

Hikmat Yar, Tanveer Hussain, Mohit Agarwal et al.

IEEE Transactions on Image Processing 2022 10.1109/tip.2022.3207006

[4]

Khan "Randomly initialized CNN with densely connected stacked autoencoder for efficient fire detection" Eng. Appl. Artif. Intell. (2022) 10.1016/j.engappai.2022.105403

[5]

Dang "Sensor-based and vision-based human activity recognition: a comprehensive survey" Pattern Recognit. (2020)

[6]

Muhammad "Efficient fire detection for uncertain surveillance environment" IEEE Trans. Ind. Inf. (2019) 10.1109/tii.2019.2897594

[7]

Optimized Dual Fire Attention Network and Medium-Scale Fire Classification Benchmark

Hikmat Yar, Tanveer Hussain, Mohit Agarwal et al.

IEEE Transactions on Image Processing 2022 10.1109/tip.2022.3207006

[8]

Yang "Preferred vector machine for forest fire detection" Pattern Recognit. (2023) 10.1016/j.patcog.2023.109722

[9]

Foggia "Real-time fire detection for video-surveillance applications using a combination of experts based on color, shape, and motion" IEEE Trans. Circuits Syst. Video Technol. (2015) 10.1109/tcsvt.2015.2392531

[10]

Chino (2015)

[11]

Celik "Fire detection in video sequences using a generic color model" Fire Saf. J. (2009) 10.1016/j.firesaf.2008.05.005

[12]

Harkat "Fire images classification based on a handcraft approach" Expert Syst. Appl. (2023) 10.1016/j.eswa.2022.118594

[13]

Mueller "Optical flow estimation for flame detection in videos" IEEE Trans. Image Process. (2013) 10.1109/tip.2013.2258353

[14]

Tao "Learning discriminative feature representation with pixel-level supervision for forest smoke recognition" Pattern Recognit. (2023) 10.1016/j.patcog.2023.109761

[15]

Muhammad "Early fire detection using convolutional neural networks during surveillance for effective disaster management" Neurocomputing (2018) 10.1016/j.neucom.2017.04.083

[16]

Huang "Fire detection in video surveillances using convolutional neural networks and wavelet transform" Eng. Appl. Artif. Intell. (2022) 10.1016/j.engappai.2022.104737

[17]

Yar "An effective attention-based CNN model for fire detection in adverse weather conditions" ISPRS J. Photogramm. Remote Sens. (2023) 10.1016/j.isprsjprs.2023.10.019

[18]

Yuan "A lightweight network for smoke semantic segmentation" Pattern Recognit. (2023) 10.1016/j.patcog.2022.109289

[19]

Yar "A modified vision transformer architecture with scratch learning capabilities for effective fire detection" Expert Syst. Appl. (2024) 10.1016/j.eswa.2024.123935

[20]

Wang "CAM-based non-local attention network for weakly supervised fire detection" Service Oriented Comput. Appl. (2022)

[21]

Majid "Attention based CNN model for fire detection and localization in real-world images" Expert Syst. Appl. (2022) 10.1016/j.eswa.2021.116114

[22]

Jiang "A self-attention network for smoke detection" Fire Saf. J. (2022) 10.1016/j.firesaf.2022.103547

[23]

Abimbola O.O., "Fire-Flame-Dataset", 2019. [Online]. Available: https://github.com/DeepQuestAI/Fire-Smoke-Dataset, Access Data: 14 September 2022.

[24]

Sharma "Deep convolutional neural networks for fire detection in images" (2017)

[25]

T.-H. Chen, P.-H. Wu, and Y.-C. Chiou, "An Early Fire-Detection Method Based On Image Processing", 2004, vol. 3: IEEE, pp. 1707–1710. 10.1109/icip.2004.1421401

[26]

D. Zhang et al., "Image Based Forest Fire Detection Using Dynamic Characteristics With Artificial Neural Networks", 2009: IEEE, pp. 290–293. 10.1109/jcai.2009.79

[27]

T. Celik, H. Ozkaramanli, and H. Demirel, "Fire Pixel Classification Using Fuzzy Logic and Statistical Color Model", 2007, vol. 1: IEEE, pp. I-1205. 10.1109/icassp.2007.366130

[28]

Habiboğlu "Covariance matrix-based fire and flame detection method in video" Mach Vis Appl (2012) 10.1007/s00138-011-0369-1

[29]

An efficient deep learning architecture for effective fire detection in smart surveillance

Hikmat Yar, Zulfiqar Ahmad Khan, Imad Rida et al.

Image and Vision Computing 2024 10.1016/j.imavis.2024.104989

[30]

Sharma (2017)

[31]

Muhammad "Convolutional neural networks based fire detection in surveillance videos" IEEE Access (2018) 10.1109/access.2018.2812835

[32]

Muhammad "Efficient deep CNN-based fire detection and localization in video surveillance applications" IEEE Transact. Systems, Man, and Cybernetics: Systems (2018) 10.1109/tsmc.2018.2830099

[33]

Jeon "Multi-scale prediction for fire detection using convolutional neural network" Fire Technol. (2021) 10.1007/s10694-021-01132-y

[34]

Khan "Energy-efficient deep CNN for smoke detection in foggy IoT environment" IEEE Int. Things J. (2019) 10.1109/jiot.2019.2896120

[35]

Deng "Multi-step implicit Adams predictor-corrector network for fire detection" IET Image Proc. (2022) 10.1049/ipr2.12491

[36]

Dilshad "Towards efficient fire detection in IoT environment: a modified attention network and large-scale dataset" IEEE Int. Things J. (2023)

[37]

Feng "Multiscale network based on feature fusion for fire disaster detection in complex scenes" Expert Syst. Appl. (2024) 10.1016/j.eswa.2023.122494

[38]

Hashemzadeh "Fire detection for video surveillance applications using ICA K-medoids-based color model and efficient spatio-temporal visual features" Expert Syst. Appl. (2019) 10.1016/j.eswa.2019.04.019

[39]

Li "A visualized fire detection method based on convolutional neural network beyond anchor" Appl. Intellig. (2022) 10.1007/s10489-021-02377-4

[40]

Avula (2020)

Metrics

16

Citations

40

References

Details

Published: May 01, 2025
Vol/Issue: 161
Pages: 111273
License: View

Authors

Z

Zulfiqar Ahmad Khan

Department of Software, Sejong University, Seoul, South Korea

Department of Software, Sejong University, Seoul, South Korea

Cite This Article

Zulfiqar Ahmad Khan, Fath U Min Ullah, Hikmat Yar, et al. (2025). Optimized cross-module attention network and medium-scale dataset for effective fire detection. Pattern Recognition, 161, 111273. https://doi.org/10.1016/j.patcog.2024.111273

Optimized cross-module attention network and medium-scale dataset for effective fire detection

You May Also Like