Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Danish Nazir"'
Publikováno v:
IEEE Access, Vol 10, Pp 120781-120791 (2022)
Depth completion involves recovering a dense depth map from a sparse map and an RGB image. Recent approaches focus on utilizing color images as guidance images to recover depth at invalid pixels. However, color images alone are not enough to provide
Externí odkaz:
https://doaj.org/article/4cdc388f284b4efb88c90b9fb2cd5870
Publikováno v:
University of Sindh Journal of Information and Communication Technology, Vol 4, Iss 3, Pp 134-138 (2020)
Externí odkaz:
https://doaj.org/article/69780f8f8a3f4edb9e9275349814c225
Autor:
Muhammad Ahmed Ullah Khan, Danish Nazir, Alain Pagani, Hamam Mokayed, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal
Publikováno v:
Sensors, Vol 22, Iss 18, p 6969 (2022)
Depth maps produced by LiDAR-based approaches are sparse. Even high-end LiDAR sensors produce highly sparse depth maps, which are also noisy around the object boundaries. Depth completion is the task of generating a dense depth map from a sparse dept
Externí odkaz:
https://doaj.org/article/32fa545fb49443c98471c4958d010b7e
Publikováno v:
Sensors, Vol 21, Iss 21, p 7392 (2021)
In this paper, we present the idea of Self Supervised learning on the shape completion and classification of point clouds. Most 3D shape completion pipelines utilize AutoEncoders to extract features from point clouds used in downstream tasks such as
Externí odkaz:
https://doaj.org/article/0692d70bba7b47738add93318f10650f
Autor:
Danish Nazir, Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal
Publikováno v:
Applied Sciences, Vol 11, Iss 18, p 8396 (2021)
Tables in document images are an important entity since they contain crucial information. Therefore, accurate table detection can significantly improve the information extraction from documents. In this work, we present a novel end-to-end trainable p
Externí odkaz:
https://doaj.org/article/6d7900003a814a96b5d7aa6f826a796e
Background: Covid-19 disease emerged nearly two and a half years back and lead to a pandemic whose severity ranged from a mild to a severe disease, those who were vaccinated had an asymptomatic infection or had a mild variety of the disease. Objectiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34e8ab30c32e0e18e7ac082805f45e02
Autor:
Danish Nazir, Ashif Ali
Publikováno v:
Global Sci-Tech. 12:148-153
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6628e5538a35f4fa18c4225caf389b6d
https://doi.org/10.5958/2455-7110.2020.00018.x
https://doi.org/10.5958/2455-7110.2020.00018.x
Autor:
Marcus Liwicki, Danish Nazir, Didier Stricker, Muhammad Zeshan Afzal, Alain Pagani, Khurram Azeem Hashmi
Publikováno v:
Applied Sciences, Vol 11, Iss 8396, p 8396 (2021)
Applied Sciences
Volume 11
Issue 18
Applied Sciences
Volume 11
Issue 18
Tables in document images are an important entity since they contain crucial information. Therefore, accurate table detection can significantly improve the information extraction from documents. In this work, we present a novel end-to-end trainable p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ed57efe0f5633b13c0622c733aa8cbf
https://www.mdpi.com/2076-3417/11/18/8396
https://www.mdpi.com/2076-3417/11/18/8396
Autor:
Danish Nazir
Publikováno v:
Global Sci-Tech. 12:14
In today’s world, web application plays a vital role by providing easy accessibility, availability, centralized and highly secured information of any system. This paper actually focuses on the Online Blood Bank System developed for the students. It
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ce98934d59d417721364d3c751c8732
https://doi.org/10.5958/2455-7110.2020.00002.6
https://doi.org/10.5958/2455-7110.2020.00002.6
Publikováno v:
Web of Science
In this paper we present a vision-based vehicle detection pipeline for autonomous vehicles. This pipeline is based on Histograms of Oriented Gradients (HOG) and Support Vector Machines (SVM) for classification. Primary motivation to conduct this rese
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6308a6ffd46a1116b1e436e9feb41487
https://doi.org/10.1109/iccce.2018.8539298
https://doi.org/10.1109/iccce.2018.8539298