Resource Efficient Perception for Vision Systems Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2405.07166
Despite the rapid advancement in the field of image recognition, the processing of high-resolution imagery remains a computational challenge. However, this processing is pivotal for extracting detailed object insights in areas ranging from autonomous vehicle navigation to medical imaging analyses. Our study introduces a framework aimed at mitigating these challenges by leveraging memory efficient patch based processing for high resolution images. It incorporates a global context representation alongside local patch information, enabling a comprehensive understanding of the image content. In contrast to traditional training methods which are limited by memory constraints, our method enables training of ultra high resolution images. We demonstrate the effectiveness of our method through superior performance on 7 different benchmarks across classification, object detection, and segmentation. Notably, the proposed method achieves strong performance even on resource-constrained devices like Jetson Nano. Our code is available at https://github.com/Visual-Conception-Group/Localized-Perception-Constrained-Vision-Systems.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2405.07166
- https://arxiv.org/pdf/2405.07166
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396913389
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4396913389Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2405.07166Digital Object Identifier
- Title
-
Resource Efficient Perception for Vision SystemsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-12Full publication date if available
- Authors
-
A V Subramanyam, Niyati Singal, Vinay Kumar VermaList of authors in order
- Landing page
-
https://arxiv.org/abs/2405.07166Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2405.07166Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2405.07166Direct OA link when available
- Concepts
-
Perception, Computer science, Resource (disambiguation), Computer vision, Artificial intelligence, Business, Psychology, Neuroscience, Computer networkTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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