MCFP-YOLO animal species detector for embedded systems

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dc.contributor.authorIbraheam, Mai
dc.contributor.authorLi, Kin Fun
dc.contributor.authorGebali, Fayez
dc.date.accessioned2024-01-24T23:12:01Z
dc.date.available2024-01-24T23:12:01Z
dc.date.copyright2023en_US
dc.date.issued2023
dc.description.abstractAdvances in deep learning have led to the development of various animal species detection models suited for different environments. Building on this, our research introduces a detection model that efficiently handles both batch and real-time processing. It achieves this by integrating a motion-based frame selection algorithm and a two-stage pipelining–dataflow hybrid parallel processing approach. These modifications significantly reduced the processing delay and power consumption of the proposed MCFP-YOLO detector, particularly on embedded systems with limited resources, without trading off the accuracy of our animal species detection system. For field applications, the proposed MCFP-YOLO model was deployed and tested on two embedded devices: the RP4B and the Jetson Nano. While the Jetson Nano provided faster processing, the RP4B was selected due to its lower power consumption and a balanced cost–performance ratio, making it particularly suitable for extended use in remote areas.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.identifier.citationIbraheam, M., Li, K. F., & Gebali, F. (2023). MCFP-yolo animal species detector for embedded systems. Electronics, 12(24), 5044. https://doi.org/10.3390/electronics12245044en_US
dc.identifier.urihttps://doi.org/10.3390/electronics12245044
dc.identifier.urihttp://hdl.handle.net/1828/15873
dc.language.isoenen_US
dc.publisherElectronicsen_US
dc.rightsAttribution 2.5 Canada*
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/ca/*
dc.subjectdeep learning
dc.subjectconvolutional neural network (CNN)
dc.subjectparallel processing
dc.subjectpipelining
dc.subjectembedded device
dc.subjectdataflow
dc.subjectanimal species detection
dc.subject.departmentDepartment of Electrical and Computer Engineering
dc.titleMCFP-YOLO animal species detector for embedded systemsen_US
dc.typeArticleen_US

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