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Fatemeh Afghah

4 papers hereh-index 234 citations6 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CV2
  • cs.LG2
same name
  • Fatemeh Afghah — 16 papers, h 12
  • Fatemeh Afghah — 7 papers, h 3
  • Fatemeh Afghah — 7 papers, h 3
  • Fatemeh Afghah — 5 papers, h 12
  • Fatemeh Afghah — 4 papers, h 1
  • Fatemeh Afghah — 4 papers, h 13

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

activity
20242026
collaborators

4 papers

cs.LG2026

RFPrompt: Prompt-Based Expert Adaptation of the Large Wireless Model for Modulation Classification

Md Raihan Uddin, Tolunay Seyfi, Fatemeh Afghah

Automatic modulation classification (AMC) in real-world deployments demands robustness to distribution shifts arising from hardware impairments, unseen propagation environments, an…

cs.LG2026

ZO-SAM: Zero-Order Sharpness-Aware Minimization for Efficient Sparse Training

Jie Ji, Gen Li, Kaiyuan Deng +2

Deep learning models, despite their impressive achievements, suffer from high computational costs and memory requirements, limiting their usability in resource-constrained environm…

cs.CV2025

Modality-Aware SAM: Sharpness-Aware-Minimization Driven Gradient Modulation for Harmonized Multimodal Learning

Hossein R. Nowdeh, Jie Ji, Xiaolong Ma +1

In multimodal learning, dominant modalities often overshadow others, limiting generalization. We propose Modality-Aware Sharpness-Aware Minimization (M-SAM), a model-agnostic frame…

cs.CV2024

Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design

Gen Li, Zhihao Shu, Jie Ji +4

Deep neural networks (DNNs) are frequently employed in a variety of computer vision applications. Nowadays, an emerging trend in the current video distribution system is to take ad…

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