Computer Vision-Based IoT Architecture for Post COVID-19 Preventive Measures

Akib, Ahsanul; Nur, Kamruddin; Saha, Suman Kumar; Srabonee, Jannatul Ferdous; Mridha, M. F.

doi:10.12720/jait.14.1.7-19

Cited by 2 publications

(2 citation statements)

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“…The proposed method filters the categories of the existing object detection dataset to pre-train the hazard detector to classify the specific categories. The pre-training dataset comes from Microsoft COCO dataset and Det-Fly dataset [14]. The pre-training focuses on 12 categories of hazard, including UAVs, various animals, digging trucks and other objects.…”

Section: Electric Power Communication Network Datasetmentioning

confidence: 99%

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RGB-W based Hazard Detection in Electric Power Communication Networks

2023

Proceedings of 2023 the 13th International Workshop on Computer Science and Engineering

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Hazard detection is an important computer vision area in electric power communication network.In this paper, we propose a hazard detection method in electric power communication network. This method turns the short-range wireless localization information into a confidence mask corresponding to the image size. The mask is able to be input into object detectors to revise confidence scores. The proposed method aims to increase the accuracy of the detections and alleviate the problems of false positives and false negatives. We design two kinds of confidence mask in order to find a better method to utilize the localization information. In addition, dataset containing specific scenes is collected to train and test the proposed method of hazard detection task in electric power communication network. Finally, this paper adopts various metrics to evaluate the effectiveness of the proposed method. The experiments demonstrate the feasibility and superiority of the proposed method in both theory and practice.

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Section: Electric Power Communication Network Datasetmentioning

confidence: 99%

“…For identity identification, [13] uses the YOLOv2 model to process the visiblelight eye images marked with the jointly partial iris and sclera region. For post COVID-19 preventive measures, [14] proposes an IoT-based architecture including the deep learning technologies and the body temperature monitor.…”

Section: Introductionmentioning

confidence: 99%