Kaan Ersahin

According to our database1, Kaan Ersahin authored at least 11 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Deep Learning-Based Identification of Arctic Ocean Boundaries and Near-Surface Phenomena in Underwater Echograms.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Detecting Underwater Discrete Scatterers in Echograms with Deep Learning-Based Semantic Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Instance Segmentation of Herring and Salmon Schools in Acoustic Echograms using a Hybrid U-Net.
Proceedings of the 19th Conference on Robots and Vision, 2022

2021
Instance Segmentation-Based Identification of Pelagic Species in Acoustic Backscatter Data.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Detecting Marine Species in Echograms via Traditional, Hybrid, and Deep Learning Frameworks.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
A Deep Learning-based Framework for the Detection of Schools of Herring in Echograms.
CoRR, 2019

2014
Satellite-based study of water quality of Chilko lake (British Columbia, Canada): Impact on Sockeye salmon.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

2010
Segmentation and Classification of Polarimetric SAR Data Using Spectral Graph Partitioning.
IEEE Trans. Geosci. Remote. Sens., 2010

2007
Segmentation of polarimetric SAR data using contour information via spectral graph partitioning.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2007

2006
Classification of Polarimetric SAR Data Using Spectral Graph Partitioning.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2006

2004
Incorporating texture information into polarimetric radar classification using neural networks.
Proceedings of the 2004 IEEE International Geoscience and Remote Sensing Symposium, 2004


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