Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System
Individuals with visual impairments often encounter substantial challenges navigating outdoor spaces due to their inability to perceive road-surface conditions. This study introduces an innovative method that harnesses deep learning to identify and categorize road surfaces, aiming to enhance the ind...
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| Format: | Article |
| Language: | English |
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University North
2025-01-01
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| Series: | Tehnički Glasnik |
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| Online Access: | https://hrcak.srce.hr/file/473454 |
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| author | Amit Chaudhary Prabhat Verma |
| author_facet | Amit Chaudhary Prabhat Verma |
| author_sort | Amit Chaudhary |
| collection | DOAJ |
| description | Individuals with visual impairments often encounter substantial challenges navigating outdoor spaces due to their inability to perceive road-surface conditions. This study introduces an innovative method that harnesses deep learning to identify and categorize road surfaces, aiming to enhance the independence and mobility of the visually impaired. Leveraging the EfficientNetB0 model as a foundational framework and employing unified spatial-channel attention, we classified road surface images captured from a wearable camera. Through rigorous training and evaluation on a substantial dataset of road images, our modified system exhibited remarkable performance, accurately identifying road surfaces with an impressive 99.39% accuracy rate. This deep learning-driven approach holds promise as a pivotal tool for improving the autonomy and safety of individuals with visual challenges by providing instantaneous feedback on road conditions. |
| format | Article |
| id | doaj-art-07623b9cddf94e0889a9afbe20b44480 |
| institution | Kabale University |
| issn | 1846-6168 1848-5588 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | University North |
| record_format | Article |
| series | Tehnički Glasnik |
| spelling | doaj-art-07623b9cddf94e0889a9afbe20b444802025-02-06T14:20:31ZengUniversity NorthTehnički Glasnik1846-61681848-55882025-01-01191172510.31803/tg-20231018184747Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection SystemAmit Chaudhary0Prabhat Verma1Harcourt Butler Technical University, Nawabganj, Kanpur, Uttar Pradesh 208002, IndiaHarcourt Butler Technical University, Nawabganj, Kanpur, Uttar Pradesh 208002, IndiaIndividuals with visual impairments often encounter substantial challenges navigating outdoor spaces due to their inability to perceive road-surface conditions. This study introduces an innovative method that harnesses deep learning to identify and categorize road surfaces, aiming to enhance the independence and mobility of the visually impaired. Leveraging the EfficientNetB0 model as a foundational framework and employing unified spatial-channel attention, we classified road surface images captured from a wearable camera. Through rigorous training and evaluation on a substantial dataset of road images, our modified system exhibited remarkable performance, accurately identifying road surfaces with an impressive 99.39% accuracy rate. This deep learning-driven approach holds promise as a pivotal tool for improving the autonomy and safety of individuals with visual challenges by providing instantaneous feedback on road conditions.https://hrcak.srce.hr/file/473454attention mechanismdeep learning networkEfficientNet-B0pedestrian with vision limitations |
| spellingShingle | Amit Chaudhary Prabhat Verma Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System Tehnički Glasnik attention mechanism deep learning network EfficientNet-B0 pedestrian with vision limitations |
| title | Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System |
| title_full | Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System |
| title_fullStr | Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System |
| title_full_unstemmed | Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System |
| title_short | Improving Freedom of Visually Impaired Individuals with Innovative EfficientNet and Unified Spatial-Channel Attention: A Deep Learning-Based Road Surface Detection System |
| title_sort | improving freedom of visually impaired individuals with innovative efficientnet and unified spatial channel attention a deep learning based road surface detection system |
| topic | attention mechanism deep learning network EfficientNet-B0 pedestrian with vision limitations |
| url | https://hrcak.srce.hr/file/473454 |
| work_keys_str_mv | AT amitchaudhary improvingfreedomofvisuallyimpairedindividualswithinnovativeefficientnetandunifiedspatialchannelattentionadeeplearningbasedroadsurfacedetectionsystem AT prabhatverma improvingfreedomofvisuallyimpairedindividualswithinnovativeefficientnetandunifiedspatialchannelattentionadeeplearningbasedroadsurfacedetectionsystem |