YOLO-FIRI: Improved YOLOv5 for Infrared Image Object Detection

To solve object detection issues in infrared images, such as a low recognition rate and a high false alarm rate caused by long distances, weak energy, and low resolution, we propose a region-free object detector named YOLO-FIR for infrared (IR) images with YOLOv5 core by compressing channels, optimi...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.141861-141875
Hauptverfasser:	Li, Shasha, Li, Yongjun, Li, Yao, Li, Mengjun, Xu, Xiaorong
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Attention mechanism Computer vision Convolutional neural networks Datasets Detectors False alarms Feature extraction Image compression Image enhancement image fusion Image processing Infrared detectors infrared image Infrared imagery Modules Object detection Object recognition Parameters Proposals Real-time systems Task analysis Weight reduction YOLOv5
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