The improved C3STR structure.

<div><p>Steel surface defect detection is an important application of object detection in industry. Achieving object detection in industry while balancing detection accuracy and real-time performance is a challenge. Therefore, this paper proposes an improved FasterNet-YOLO model based on...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Shiwei Yu (6060308) (author)
مؤلفون آخرون:	Zelin Liu (2077912) (author), Liang Zhang (41392) (author), Xiaoqiang Zhang (2413909) (author), Jikui Wang (4519225) (author)
منشور في:	2025
الموضوعات:	Sociology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified also significantly improves detector &# 8217 depthwise separable convolution 4 %, gflops yolov5 backbone network reducing redundant parameters achieving object detection balancing detection accuracy improve model accuracy improve detection speed yolo model based object detection detection accuracy stage detector ordinary convolution 2 %, time detection detection speed original model model lightweighting neck network fasternet network improved model time performance slight reduction significant improvement results indicated paper proposes informative features important application fps increased feature fusion easy confusion different scales defect types defect photographs cluttered backgrounds c3 module 1 %.
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

The improved C3STR structure.

مواد مشابهة