SENET-D: Efficient Semantic Segmentation for RGB-Depth food images

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SPIRE - Sciences Po Institutional REpository
Published
2024-09-21
Primary Topic
Image Retrieval and Classification Techniques
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article
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article

SENET-D: Efficient Semantic Segmentation for RGB-Depth food images

Eugène Sobngwi, Pierre Ele, Lotfi Chaâri, Thierry Roland Baban A Erep
SPIRE - Sciences Po Institutional REpository
Image Retrieval and Classification Techniques
article

SENET-D: Efficient Semantic Segmentation for RGB-Depth food images

Eugène Sobngwi, Pierre Ele, Lotfi Chaâri, Thierry Roland Baban A Erep
article en

Abstract

No abstract available for this paper.
SPIRE - Sciences Po Institutional REpository
Université Toulouse III - Paul Sabatier (FR), Institut National Polytechnique de Toulouse (FR), Université Toulouse-I-Capitole (FR), Central Hospital of Yaoundé (CM), Institut de Recherche en Informatique de Toulouse (FR), Université Toulouse - Jean Jaurès (FR), Institut Polytechnique de Bordeaux (FR)
Zero hunger
Openalex Percentile: Top 85%
Image Retrieval and Classification Techniques
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