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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
Issue per Year : 12
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Issue Published : 120
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Total Authors : 24597
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| Paper Title: | Road Extraction from DeepGlobe Satellite Imagery Using a U-Net–Based Deep Learning Model |
| Authors Name: | Dr.Mohd Jawed Khan , Divyansh Singh Rajpoot , Ravinder Yadav , Ashutosh Kumar |
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IJRTI_212115
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| Published Paper Id: | IJRTI2604288 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | Accurate road extraction from high-resolution satellite imagery is essential for modern Geographic Information Systems (GIS), urban planning, navigation, and disaster-response applications. However, satellite images often present considerable challenges such as occlusion, noise, varying illumination, and the presence of thin or fragmented road segments. To address these limitations, this study proposes an enhanced U-Net–based semantic segmentation framework trained on the DeepGlobe Road Extraction Dataset. The methodology integrates advanced preprocessing techniques, including normalization, morphological enhancement, and patch-based extraction, along with extensive data augmentation to improve model robustness. A hybrid loss function combining Binary Cross-Entropy and Dice Loss is implemented to effectively tackle class imbalance and improve thin-road detection. Experimental results demonstrate that the proposed model achieves strong performance, with an IoU of 0.78 and a Dice score of 0.85, outperforming baseline models such as FCN-8 and SegNet. Visual evaluations further confirm the model’s ability to extract continuous, high-precision road networks even in complex environments. The outcomes highlight the effectiveness of U-Net for satellite-based road segmentation and emphasize its potential for real- world applications in map updating, intelligent transportation systems, and post-disaster infrastructure assessment. |
| Keywords: | Road Extraction, U-Net, Semantic Segmentation, Deep Learning, Remote Sensing. |
| Cite Article: | "Road Extraction from DeepGlobe Satellite Imagery Using a U-Net–Based Deep Learning Model", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c101-c112, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604288.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604288
Registration ID:212115
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: c101-c112 Country: GREATER NOIDA, UTTAR PRADESH, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604288 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604288 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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