An Ensemble Convolutional Neural Networks for Detection of Growth Anomalies in Children with X-ray Images

H. Sarabi Sarvarani; F. Abdali-Mohammadi

Volume 10, Issue 4 , November 2022, , Pages 479-492

https://doi.org/10.22044/jadm.2022.11752.2323

Abstract
  Bone age assessment is a method that is constantly used for investigating growth abnormalities, endocrine gland treatment, and pediatric syndromes. Since the advent of digital imaging, for several decades the bone age assessment has been performed by visually examining the ossification of the left hand, ...  Read More

H.3. Artificial Intelligence
Hand Gesture Recognition from RGB-D Data using 2D and 3D Convolutional Neural Networks: a comparative study

M. Kurmanji; F. Ghaderi

Volume 8, Issue 2 , April 2020, , Pages 177-188

https://doi.org/10.22044/jadm.2019.7903.1929

Abstract
  Despite considerable enhances in recognizing hand gestures from still images, there are still many challenges in the classification of hand gestures in videos. The latter comes with more challenges, including higher computational complexity and arduous task of representing temporal features. Hand movement ...  Read More