Zobrazeno 1 - 10
of 169
pro vyhledávání: '"Durga Toshniwal"'
Publikováno v:
Geoscience Data Journal, Vol 11, Iss 4, Pp 846-862 (2024)
Abstract The data article describes the Road Damage Dataset, RDD2022, encompassing of 47,420 road images from majorly six countries, Japan, India, the Czech Republic, Norway, the United States, and China. The dataset incorporates over 55,000 instance
Externí odkaz:
https://doaj.org/article/e1eae055bd7b4891b7418b49890bcca2
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Accurate prediction of Dissolved Oxygen (DO) is an integral part of water resource management. This study proposes a novel approach combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) with AdaBoost and deep
Externí odkaz:
https://doaj.org/article/5b471969488c4baca34b5b7830dab8e2
Autor:
Aarzoo Dhiman, Durga Toshniwal
Publikováno v:
IEEE Access, Vol 8, Pp 122168-122184 (2020)
The abundance and real-time availability of Twitter data have proved beneficial in detecting events in various domains such as emergency situations, crime detection, public health, place recommendations, etc. Nevertheless, two critical challenges occ
Externí odkaz:
https://doaj.org/article/6136dae3eda4430f8cf3bfd13a43c326
Publikováno v:
Data in Brief, Vol 36, Iss , Pp 107133- (2021)
This data article provides details for the RDD2020 dataset comprising 26,336 road images from India, Japan, and the Czech Republic with more than 31,000 instances of road damage. The dataset captures four types of road damage: longitudinal cracks, tr
Externí odkaz:
https://doaj.org/article/6a42fd94c9e04a1e8a7abbc94231ba38
Autor:
Amit Agarwal, Durga Toshniwal
Publikováno v:
IEEE Access, Vol 7, Pp 66536-66552 (2019)
The adequacy of traditional transport related issues detection is often limited by physical sparse sensor coverage and reporting incident/issues to the emergency response system is labor intensive. The social media tweet text have been mined so as to
Externí odkaz:
https://doaj.org/article/04092b04be8b43c1b0505655287ce4c6
Autor:
Apeksha Aggarwal, Durga Toshniwal
Publikováno v:
IEEE Access, Vol 7, Pp 98921-98933 (2019)
With the advent of big data era, enormous volumes of data are generated every second. Varied data processing algorithms and architectures have been proposed in the past to achieve better execution of data mining algorithms. One such algorithm is extr
Externí odkaz:
https://doaj.org/article/eea8f159092d49858f390229b70ab2c6
Autor:
Jatin Bedi, Durga Toshniwal
Publikováno v:
IEEE Access, Vol 6, Pp 49144-49156 (2018)
Electricity is of great significance for national economic, social, and technological activities, such as material production, healthcare, and education. The nationwide electricity demand has grown rapidly over the past few decades. Therefore, effici
Externí odkaz:
https://doaj.org/article/87a9c45c391b4de5b869cf914c6db22b
Autor:
Sachin Kumar, Durga Toshniwal
Publikováno v:
European Transport Research Review, Vol 9, Iss 2, Pp 1-10 (2017)
Abstract Objective Powered Two Wheeler (PTW) vehicles are one of the preferred modes of transport used in India. Also, PTWs accidents are comparatively more frequent than other type of accidents on road. The influencing factors of PTW accidents are a
Externí odkaz:
https://doaj.org/article/8bbb33bfd2154cde9e9f58767ba32647
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 12 (2016)
The present work focuses on predicting users' next place of visit using their past tweets. We hypothesize that tweets of the person have predictive power on his location and therefore can be used to predict his next place of visit. This problem is im
Externí odkaz:
https://doaj.org/article/e8e97dd42e47475e8c6f240377d57e35
Publikováno v:
IEEE Sensors Journal. 23:7207-7216
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b63addaf8f9092262cc695c85ecc6fb4
https://doi.org/10.1109/jsen.2023.3243230
https://doi.org/10.1109/jsen.2023.3243230