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Authors: Zhan, Huawei | Pei, Xinyu | Zhang, Tianhao | Zhang, Linqing

Article Type: Research Article

Abstract: A flame detection algorithm based on the improved SSD (Single Shot Multibox Detector) is proposed in response to the issues with the limited detection distance, delayed reaction, and high false alarm rate of previous flame detection systems. First, the ResNet-50-SPD model was added to the original backbone network to improve the detection of low resolution and tiny objects. After that, incorporate feature fusion between layers to improve the bond between contexts. Before the feature entered the prediction, the impact of channel number reduction was eliminated using the adaptive module AAM. According to experimental findings, the modified SSD algorithm’s mAP value …on on the random division dataset and K-fold verification dataset reaches 87.89% and 89.63%, respectively, which is 3.97% and 5.17% higher than the original SSD, while the FPS remains at 64.9 f/s. It is helpful to improve the time of the fire alarm, find the ignition point in time, and better meet the actual engineering needs of fire monitoring. Show more

Keywords: Flame detection, SSD, ResNet-50-SPD, feature fusion, AAM

DOI: 10.3233/JIFS-232645

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 6501-6512, 2023

Authors: Zhan, Huawei | Li, Junjie | Wei, Gaoyong | Han, Chengju

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-236836

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 4, pp. 8139-8151, 2024

Authors: Zhan, Huawei | Han, Chengju | Li, Junjie | Wei, Gaoyong

Article Type: Research Article

Abstract: Aiming at the problems of slow speed and low accuracy of traditional neural network systems for real-time gesture recognition in complex backgrounds., this paper proposes DMS-yolov8-a gesture recognition method to improve yolov8. This algorithm replaces the Bottleneck convolution module in the backbone network of yolov8 with variable row convolution DCNV2, and increases the feature convolution range without increasing the computation amount through a more flexible feeling field. in addition, the self-developed MPCA attention module is added after the feature output layer of the backbone layer, which improves the problem of recognizing the accuracy of difference gestures in complex backgrounds by …effectively combining the feature information of the contextual framework, taking into account the multi-scale problem of the gestures in the image, this paper introduces the SPPFCSPS module, which realizes multi-feature fusion and improves real-time accuracy of detection. Finally, the model proposed in this paper is compared with other models, and the proposed DMS-yolov8 model achieves good results on both publicly available datasets and homemade datasets, with the average accuracy up to 97.4% and the average mAP value up to 96.3%, The improvements proposed in this paper are effectively validated. Show more

Keywords: Gesture recognition, yolov8, DCNV2, MPCA, feature fusion

DOI: 10.3233/JIFS-238629

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024