Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
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
An Artificial Neural Network Based Pixel-by-Pixel Lossless Image Compression Method
Date
2022-05-15
Author
Kamışlı, Fatih
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
144
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/98912
DOI
https://doi.org/10.1109/siu55565.2022.9864886
Conference Name
2022 30th Signal Processing and Communications Applications Conference (SIU)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
An adaptive mobile cloud computing framework using a call graph based model
Kaya, Mahir; Koçyiğit, Altan; Eren, Pekin Erhan (2016-04-01)
The use of mobile applications and their functionality are increasing day by day but mobile devices are still inferior to ordinary computers in terms of memory and processor capacity. Furthermore, the rapid depletion of the mobile devices' energy is still a major problem. Performance and energy shortcomings of mobile devices can be improved by using surrogate or cloud computing technologies. In particular, computation and memory intensive real time applications would be efficiently run by utilizing the reso...
An FPGA based high performance optical flow hardware design for autonomous mobile robotic platforms
Gültekin, Gökhan Koray; Saranlı, Afşar; Department of Electrical and Electronics Engineering (2010)
Optical flow is used in a number of computer vision applications. However, its use in mobile robotic applications is limited because of the high computational complexity involved and the limited availability of computational resources on such platforms. The lack of a hardware that is capable of computing optical flow vector field in real time is a factor that prevents the mobile robotics community to efficiently utilize some successful techniques presented in computer vision literature. In this thesis work,...
An iterative hydraulic design methodology based on numerical modeling for piano key weirs
Köken, Mete; Aydın, İsmail; Ademoglu, Serhan (2022-01-01)
Piano Key Weir (PKW) is a special type of overflow weir which provides an improved discharge capacity with its increased crest length. Increased discharge capacity makes this weir an attractive alternative in the rehabilitation of existing spillways. After the introduction of this new weir type, many experimental and numerical studies are conducted to understand the effect of the numerous geometrical parameters on the discharge capacity. However, empirical discharge formulas suggested by different researche...
An interactive sorting approach based on information theoretic measure
Özarslan, Ali; Karakaya, Gülşah (null; 2019-06-16)
In this study, we develop an interactive approach for sorting alternatives. We assume that the preferences of the decision maker are consistent with an additive function. We assign worst and best possible categories for each alternative and narrow down these category ranges using mixed integer programming (MIP) iteratively. We utilize binary variables to assign the alternatives for which the classes are not known exactly. We incorporate the worst and best possible category information to the MIPs whenever n...
A hybrid swarm intelligence algorithm for simultaneous feature selection and clustering
Geren, Hasan; Özdemirel, Nur Evin; Department of Industrial Engineering (2022-6-20)
In this study, we address the feature selection and clustering problems by using a hybrid swarm intelligence approach. We assume that the number of clusters is known, clusters can be of any shape and have different densities, but there are no outliers or noise. The data set may have high dimensionality and redundant features. We propose a swarm intelligence algorithm, namely ACOVNS, which is a hybridization of Ant Colony Optimization (ACO) and Variable Neighborhood Search (VNS). We utilize the ACO mechanism...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
F. Kamışlı, “An Artificial Neural Network Based Pixel-by-Pixel Lossless Image Compression Method,” presented at the 2022 30th Signal Processing and Communications Applications Conference (SIU), Karabük, Türkiye, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/98912.