|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: April 2024
Volume 9 | Issue 4
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 95
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | SURVEY ON POTHOLE DETECTION AND COMPLAINT MANAGEMENT SYSTEM USING DEEP LEARNING |
| Authors Name: | Shubham Tanaji Barangule , Nandakishor Ankush More , Omkar Tanaji Mote , Abhishek Tanaji Doke , Prof.Arunadevi Khaple |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_196083
|
| Published Paper Id: | IJNRD2305570 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Potholes are a common problem in road maintenance, which can cause serious accidents and damages to vehicles. Traditional methods of pothole detection involve manual inspections, which are time-consuming, costly, and often result in missing some potholes. In recent years, the development of pothole detection systems using convolutional neural networks (CNNs) has shown great potential to improve road maintenance efficiency. This survey paper provides an overview of the recent advancements in the pothole detection system using CNNs. The paper discusses the state-of-the-art techniques and their limitations, as well as the challenges and future directions in this field. The survey paper reviews several state-of-the-art techniques in pothole detection using CNNs, including YOLOv4, Faster R-CNN, and Mask R-CNN. The paper also highlights the challenges in this field, including the limited availability of datasets and the need for real-time processing algorithms that can run on low-power devices. The survey paper concludes by emphasising the significance of pothole detection systems using CNNs in improving road safety, reducing repair costs, and improving the overall infrastructure. |
| Keywords: | Pothole detection, Convolutional neural networks, Deep learning, Road maintenance, Image processing |
| Cite Article: | "SURVEY ON POTHOLE DETECTION AND COMPLAINT MANAGEMENT SYSTEM USING DEEP LEARNING", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.f463-f465, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305570.pdf |
| Downloads: | 000118753 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2305570 Registration ID: 196083 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: f463-f465 Country: Pune, maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305570 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305570 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn