Age and gender classification with bone images using deep learning algorithms
Sathyavathi Sundarasamy,
Baskaran Kuttuva Rajendran
Abstract:In paediatrics, bone age is a crucial indicator of how a child's skeleton is developing. They have had great success ever since the creation of deep learning (DL)-based bone age prediction tools. Deep features learning, however, has a significant computing overhead problem. Deep convolution layers are used in this technique to learn representative features in the small yet useful regions that are extracted for feature learning. This work suggests using an extreme learning machine algorithm as the fundamental a… Show more
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