DeepSperm: A robust and real-time bull sperm-cell detection in densely populated semen videos

Background and Objective: Object detection is a primary research interest in computer vision. Sperm-cell detection in a densely populated bull semen microscopic observation video presents challenges such as partial occlusion, vast number of objects in a single video frame, tiny size of the object, a...

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Veröffentlicht in:	arXiv.org 2020-03
Hauptverfasser:	Priyanto Hidayatullah, Wang, Xueting, Yamasaki, Toshihiko, Tati L E R Mengko, Rinaldi Munir, Barlian, Anggraini, Sukmawati, Eros, Supraptono, Supraptono
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Computer architecture Computer vision Datasets Graphics processing units Image detection Image processing Object recognition Occlusion Parameters Real time Saturation (color) Semen Sperm Training
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