all AI news
Image Coding for Machines with Edge Information Learning Using Segment Anything
March 8, 2024, 5:45 a.m. | Takahiro Shindo, Kein Yamada, Taiju Watanabe, Hiroshi Watanabe
cs.CV updates on arXiv.org arxiv.org
Abstract: Image Coding for Machines (ICM) is an image compression technique for image recognition.
This technique is essential due to the growing demand for image recognition AI.
In this paper, we propose a method for ICM that focuses on encoding and decoding only the edge information of object parts in an image, which we call SA-ICM.
This is an Learned Image Compression (LIC) model trained using edge information created by Segment Anything.
Our method can be …
abstract arxiv coding compression cs.cv decoding demand edge encoding image image recognition information machines paper recognition segment segment anything the edge type
More from arxiv.org / cs.CV updates on arXiv.org
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
1 day, 12 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Global Data Architect, AVP - State Street Global Advisors
@ State Street | Boston, Massachusetts
Data Engineer
@ NTT DATA | Pune, MH, IN