CNN-Based Object Recognition and Tracking System to Assist Visually Impaired People
Visually impaired persons (VIPs) comprise a significant portion of the population, and they are present around the globe and in every part of the world. In recent times, technology proved its presence in every domain, and innovative devices assist humans in their daily lives. In this work, a smart a...
Saved in:
| Main Authors: | Fahad Ashiq, Muhammad Asif, Maaz Bin Ahmad, Sadia Zafar, Khalid Masood, Toqeer Mahmood, Muhammad Tariq Mahmood, Ik Hyun Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9698080/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Assistive Devices Analysis for Visually Impaired Persons: A Review on Taxonomy
by: Sadia Zafar, et al.
Published: (2022-01-01) -
Content oriented 3D-CNN sequence learning architecture for academic activities recognition using a realistic CAD dataset
by: Muhammad Wasim, et al.
Published: (2025-07-01) -
Blockchain-Enabled VANET for Smart Solid Waste Management
by: Muhammad Saad, et al.
Published: (2023-01-01) -
Handwritten Urdu Characters and Digits Recognition Using Transfer Learning and Augmentation With AlexNet
by: Aqsa Rasheed, et al.
Published: (2022-01-01) -
Bangla Speech Emotion Recognition and Cross-Lingual Study Using Deep CNN and BLSTM Networks
by: Sadia Sultana, et al.
Published: (2022-01-01)