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سی و چهارمین کنفرانس بین المللی مهندسی برق
Entangled multiscale neural network for semantic segmentation of blastocysts
نویسندگان :
Salar Abbasi
1
Mehdi Sojoodi
2
1- دانشگاه تربیت مدرس
2- دانشگاه تربیت مدرس
کلمات کلیدی :
Convolutional Neural networks،Semantic segmentation of blastocyst،Quantum attention mechanism،Embryology
چکیده :
In embryology and IVF labs, embryologist’s analysis of blastocyst images is central to artificial fertilization processes. Traditional methods relied on subjective, experience based visual inspection to classify healthy versus unhealthy blastocysts by tissue morphology, but these were time consuming and prone to errors. This study introduces a neural network model for detecting and semantically segmenting cellular tissues in blastocyst images, featuring a multi-scale architecture and quantum attention mechanisms to extract richer features and focus on fine details, yielding higher accuracy.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.7.2
