Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild
Date
2020-12-01
Author
Kurnaz, Fatih Can
Hocaoğlu, Burak
Yılmaz, Mert Kaan
Sülo, İdil
Kalkan, Sinan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
227
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/94058
Conference Name
ECCV2020 International Workshop on Assistive Computer Vision and Robotics
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Alet (automated labeling of equipment and tools): A dataset for tool detection and human worker safety detection
Kurnaz, Fatih Can; Şahin, Erol; Kalkan, Sinan; Department of Computer Engineering (2020-8)
For humans and robots to be able to collaborate in different tasks in the same real-life environments, robots need to be able to work with tools. This requires that they can recognize the tools, and identify their positions and orientations so that they can use them for their goals. However, neither robotics nor the computer vision community had a dataset to facilitate addressing these problems in real-life environments. In this study, we address these challenges and provide a dataset dedicated to detecting...
ISAC for information system development and an application
Tubaishat, Abdullah; Aktaş, Ziya; Department of Computer Engineering (1988)
EFES: An Effort Estimation Methodology
Tunalilar, Seckin; Demirörs, Onur (2012-10-19)
The estimation of effort is at the heart of project tasks, since it is used for many purposes such as cost estimation, budgeting, monitoring, project planning, control and software investments. Researchers analyze problems of the estimation, propose new models and use new techniques to improve estimation accuracy. However, effort estimation problem is not only computational but also a managerial problem and we need a defined estimation methodology to guide companies in their effort estimation tasks. Managem...
Efes: an effort estimation methodology
Tunalılar, Seçkin; Demirörs, Onur; Department of Information Systems (2011)
The estimation of effort is at the heart of project tasks, since it is used for many purposes such as cost estimation, budgeting, monitoring, project planning, control and software investments. Researchers analyze problems of the estimation, propose new models and use new techniques to improve accuracy. However up to now, there is no comprehensive estimation methodology to guide companies in their effort estimation tasks. Effort estimation problem is not only a computational but also a managerial problem. I...
MPC-Graph: Nonlinear feedback motion planning using sparse sampling based neighborhood graph
Atasoy, Simay; Ankaralı, Mustafa Mert; Department of Electrical and Electronics Engineering (2022-1)
Robust and safe feedback motion planning and navigation is a critical task for autonomous mobile robotic systems considering the highly dynamic and uncertain nature scenarios of modern applications. For these reasons motion planning and navigation algorithms that have deep roots in feedback control theory has been at the center stage of this domain recently. However, the vast majority of such policies still rely on the idea that a motion planner first generates a set of open-loop possibly time-dependent tra...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
F. C. Kurnaz, B. Hocaoğlu, M. K. Yılmaz, İ. Sülo, and S. Kalkan, “ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild,” presented at the ECCV2020 International Workshop on Assistive Computer Vision and Robotics, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/94058.