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Edi Prifti

Institut de Recherche pour le Developpement

4 papers hereh-index 3320.1k citations98 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.SP1
affiliations
  • Institut de Recherche pour le Developpement
ORCID 0000-0001-8861-1305
same name
  • Edi Prifti — 3 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2026

AT-ViT: Area-Targeted Multi-View Vision Transformer with Cross-Attention and Multi-Scale Patching for Plant Trait Recognition in Herbarium Images

Amani Sedrat, Takieddine Chehhat, Youcef Sklab +6

Automated plant traits recognition from herbarium images is essential for plant sciences, yet remains challenging because background elements (e.g., textual labels, mounting artifa…

cs.CV2025

SIM-Net: A Multimodal Fusion Network Using Inferred 3D Object Shape Point Clouds from RGB Images for 2D Classification

Youcef Sklab, Hanane Ariouat, Eric Chenin +2

We introduce the Shape-Image Multimodal Network (SIM-Net), a novel 2D image classification architecture that integrates 3D point cloud representations inferred directly from RGB im…

cs.CV2025

IKrNet: A Neural Network for Detecting Specific Drug-Induced Patterns in Electrocardiograms Amidst Physiological Variability

Ahmad Fall, Federica Granese, Alex Lence +5

Monitoring and analyzing electrocardiogram (ECG) signals, even under varying physiological conditions, including those influenced by physical activity, drugs and stress, is crucial…

eess.SP2025

ECGrecover: a Deep Learning Approach for Electrocardiogram Signal Completion

Alex Lence, Federica Granese, Ahmad Fall +4

In this work, we address the challenge of reconstructing the complete 12-lead ECG signal from its incomplete parts. We focus on two main scenarios: (i) reconstructing missing signa…

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