id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ispiv-182	Dreisbach, Maximilian; Leister, Robin; Probst, Matthias; Friederich, Pascal; Stroh, Alexander; Kriegseis, Jochen	Particle Detection by means of Machine Learning in Defocusing PTV	2021	2	.pdf	application/pdf	1249	39	36	In experiments on synthetic images and artificial particle images produced through a pinhole aperture RetinaNet achieves a higher accuracy than the Hough transformation. [px] In te ns ity [- ] Synthetic MUNIT Real (b) Radial intensity distribution - 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.25 0.5 M is s ra te [- ] Faster R-CNN Hough RetinaNet - 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 1 2 Overlap [IoU] σ D [p x] (c) Results on overlapping particles Figure 2: (a) Random synthetic (Da), real and translation refined particle images (Db) at ascending diam- eters; (b) averaged radial intensity profiles of synthetic (Da) and refined synthetic (Db) and real particle images with a diameter of D = 22.5±0.025px; (c) miss rate and uncertainty in diameter determination σD on synthetic particle images with increasing relative overlap, measured by intersection over union (IoU).	cache/ispiv-182.pdf	txt/ispiv-182.txt