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Akbar Karimi

16 papers hereh-index 8580 citations22 works total

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

author position
  • first author5
  • middle author7
  • last author3

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CL9
  • cs.CV4
  • cs.LG2
  • cs.IR1
same name
  • Akbar Karimi — 9 papers, h 2

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
20172025
most citedA novel Region of Interest Extraction Layer for Instance Segmentation

88 citations · 140 across the 15 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CL2020★ 28 cited

Improving BERT Performance for Aspect-Based Sentiment Analysis

Akbar Karimi, Leonardo Rossi, Andrea Prati

Aspect-Based Sentiment Analysis (ABSA) studies the consumer opinion on the market products. It involves examining the type of sentiments as well as sentiment targets expressed in p…

cs.CV2020★ 88 cited

A novel Region of Interest Extraction Layer for Instance Segmentation

Leonardo Rossi, Akbar Karimi, Andrea Prati

Given the wide diffusion of deep neural network architectures for computer vision tasks, several new applications are nowadays more and more feasible. Among them, a particular atte…

cs.IR2020

Deep Multimodal Image-Text Embeddings for Automatic Cross-Media Retrieval

Hadi Abdi Khojasteh, Ebrahim Ansari, Parvin Razzaghi +1

This paper considers the task of matching images and sentences by learning a visual-textual embedding space for cross-modal retrieval. Finding such a space is a challenging task si…

cs.LG2020

Adversarial Training for Aspect-Based Sentiment Analysis with BERT

Akbar Karimi, Leonardo Rossi, Andrea Prati

Aspect-Based Sentiment Analysis (ABSA) deals with the extraction of sentiments and their targets. Collecting labeled data for this task in order to help neural networks generalize…

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