id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-2549	He, Xun; Liu, Xiaofang	Improved Angle Steel Character Detection Algorithm Based on DBNet	2022	6	.pdf	application/pdf	3222	154	50	The experimental results show that, compared with the original DBNet algorithm, the detection index of the improved DBNet algorithm is increased from 81.42% to 99.06% on the angle steel character data set, which meets the needs of angle steel character detection in the industrial environment. The final index and effect observation show that the proposed improved method is significantly improved compared with the original algorithm, which meets the requirements of industrial angle steel character detection accuracy and provides a reference for industrial angle steel character detection methods.	cache/ajst-2549.pdf	txt/ajst-2549.txt