摘要： 針對(duì)通用目標(biāo)檢測(cè)算法在檢測(cè)小目標(biāo)時(shí)存在錯(cuò)檢和漏檢等問題,提出了一種小目標(biāo)檢測(cè)算法IPH(Involution Prediction Head)，將其運(yùn)用在YOLOv4和YOLOv5的檢測(cè)頭部分,，在VOC2007數(shù)據(jù)集上的實(shí)驗(yàn)結(jié)果表明,，運(yùn)用IPH后的YOLOv4小目標(biāo)檢測(cè)精度APs(AP for small objects)相比原始算法提升了1.1%，在YOLOv5上的APs更是提升了5.9%,。經(jīng)智能交通檢測(cè)數(shù)據(jù)集進(jìn)一步檢驗(yàn),，IPH算法和去下采樣能有效提升小目標(biāo)檢測(cè)精度，減少錯(cuò)檢和漏檢的情況,。
中圖分類號(hào)： TP391.4 文獻(xiàn)標(biāo)識(shí)碼： A DOI：10.16157/j.issn.0258-7998.223161 中文引用格式： 安鶴男,，鄧武才，管聰,，等. 基于Involution Prediction Head的小目標(biāo)檢測(cè)算法[J].電子技術(shù)應(yīng)用,，2022，48(11)：19-23. 英文引用格式： An Henan,，Deng Wucai,，Guan Cong，et al. Small object detection algorithm based on involution prediction head[J]. Application of Electronic Technique,，2022,，48(11)：19-23.
Small object detection algorithm based on involution prediction head
An Henan1，Deng Wucai1,，Guan Cong2,，Jiang Bangyan2
1.College of Electronics and Information Engineering，Shenzhen University,，Shenzhen 518000,，China； 2.Institute of Microscale Optoelectronics,，Shenzhen University,，Shenzhen 518000，China
Abstract： Aiming at the problems of false positive detection and low recall in the detection of small targets by the general target detection algorithm, a small target detection algorithm IPH(involution prediction head) is proposed, which is applied to the detection head of YOLOv4 and YOLOv5. The experimental results on the VOC2007 data set show that the detection accuracy APs(AP for small objects) of YOLOv4 after using IPH is improved by 1.1% compared with the original algorithm, and the APs on YOLOv5 is improved by 5.9%. Through further verification of the intelligent traffic detection data set, IPH algorithm and desampling can effectively improve the accuracy of small object detection and reduce false positive detection and missed detection.
Key words : YOLOv4,；involution prediction head,；small object detection；feature extraction,；attention module
