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
Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
Date
2022-07-02
Author
Akyön, Fatih
Altınuç, Sinan Onur
Temizel, Alptekin
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
284
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/98054
Conference Name
IEEE International Conference on Image Processing (ICIP)
Collections
Graduate School of Informatics, Conference / Seminar
Suggestions
OpenMETU
Core
Depth assisted object segmentation in multi-view video
Cigla, Cevahir; Alatan, Abdullah Aydın (2008-01-01)
In this work, a novel and unified approach for multi-view video (MVV) object segmentation is presented. In the first stage, a region-based graph-theoretic color segmentation algorithm is proposed, in which the popular Normalized Cuts segmentation method is improved with some modifications on its graph structure. Segmentation is obtained by recursive bi-partitioning of a weighted graph of an initial over-segmentation mask. The available segmentation mask is also utilized during dense depth map estimation ste...
Scheduling for flexible layout.
Süer, Ahmet Gürsel; Department of Industrial Engineering (1985)
Waterfall region analysis for iterative decoding
Yılmaz, Ali Özgür (2004-12-01)
Finite length analysis of iterative decoders can be done by using probabilistic models based on EXIT charts. The validity of these models will be investigated by checking the performance of iterative decoding under various scenarios.
Selective max-min algorithm for low-density parity-check decoding
Hareedy, Ahmed; Khairy, Mohamed M. (2013-05-21)
With the growing importance of error correction in different communication systems, using an efficient and easily implementable code is always appreciated. One of the most important codes is the low-density parity-check (LDPC) code. Two main iterative decoding algorithms are usually used, namely the sum-product (SP) algorithm (also referred to as belief propagation) and the min-sum (MS). The SP algorithm is more accurate but suffers from very high complexity. On the other hand, the MS algorithm has a much l...
Querying Class-Relationship Logic in a Metalogic Framework
Nilsson, Jorgen Fischer (2011-10-28)
We introduce a class relationship logic for stating various forms of logical relationships between classes. This logic is intended for ontologies and knowledge bases and combinations thereof. Reasoning and querying is conducted in the DATALOC logical language, which serves as an embracing decidable and tractable metalogic.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
F. Akyön, S. O. Altınuç, and A. Temizel, “Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection,” presented at the IEEE International Conference on Image Processing (ICIP), Bordeaux, Fransa, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/98054.