@Article{jnm.2021.017763,
AUTHOR = {Jiancheng Zou, Na Zhu, Bailin Ge, Don Hong},
TITLE = {Elderly Fall Detection Based on Improved SSD Algorithm},
JOURNAL = {Journal of New Media},
VOLUME = {3},
YEAR = {2021},
NUMBER = {1},
PAGES = {1--10},
URL = {http://www.techscience.com/JNM/v3n1/41729},
ISSN = {2579-0129},
ABSTRACT = {We propose an improved a single-shot detector (SSD) algorithm to 
detect falls of the elderly. The VGG16 network part of the SSD network is 
replaced with the MobilenetV2 network. At the same time, we change the 
infrastructure of MobilenetV2 network, the three layers that were not downsampled at the end were removed, which can make the model structure simpler 
and faster to detect. The complete Intersection-over-Union (CIoU) loss function 
is introduced to get a good regression of the target borders that have different 
sizes and different proportions. We use Feature Pyramid Network (FPN) for upsampling, it can fuse low-level feature maps with high resolution and high-level 
feature maps with rich semantic information. For sampling results, we use the 
Secure Shell (SSH) module to extract different receptive fields, which improves 
the detection accuracy. Our model ensures that the accuracy of the elderly fall 
detection remains unchanged, but it greatly improves the detection speed that 
only takes 10 milliseconds to detect a picture.},
DOI = {10.32604/jnm.2021.017763}
}