Research Article
Alternate Vision Assistance Using Deep Learning
@INPROCEEDINGS{10.4108/eai.27-2-2020.2303117, author={Shameen Basharat and Sapna Jain}, title={Alternate Vision Assistance Using Deep Learning}, proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2021}, month={3}, keywords={visual debilitation computer vision innovations object identification deep learning object location structure caffe model}, doi={10.4108/eai.27-2-2020.2303117} }
- Shameen Basharat
Sapna Jain
Year: 2021
Alternate Vision Assistance Using Deep Learning
ICIDSSD
EAI
DOI: 10.4108/eai.27-2-2020.2303117
Abstract
Visual weakness and visual deficiency brought about by different illness has been enormously diminished, yet danger of age-related or intrinsic visual hindrance still hovers. Visual data is the reason for most acknowledge errands, so disabled individuals battle a great deal since they fail to get essential data about the present condition. Preforming every day movement can be particularly troublesome; it is difficult for the oblivious in regards to know about environment. With the ongoing advances in innovation it is conceivable to stretch out the help given to individuals with visual debilitation during their development. PC vision advancements, particularly the profound convolutional neural system, have recently evolved. It is promising to utilize the condition of –craftsmanship PC vision strategies to help individuals with vision misfortune. In this exploration venture, I will in general give a continuous article recognition and position estimation pipeline, with the objective of advising the client about encompassing item and their spatial position utilizing binaural sound. Towards the end, different promising bearings are examined to fill in as rules for future work in the field of object identification and neural system based learning frameworks.