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Hossein Soleimani

4 papers hereh-index 5141 citations11 works total

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

author position
  • first author2
  • last author2

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

fields
  • cs.CV2
  • cs.LG1
  • stat.ML1
same name
  • Hossein Soleimani — 7 papers, h 5
  • Hossein Soleimani — 6 papers, h 2
  • Hossein Soleimani — 2 papers, h 4
  • Hossein Soleimani — 1 paper, h 7
  • Hossein Soleimani — 1 paper, 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

activity
20142023
most citedATD: Anomalous Topic Discovery in High Dimensional Discrete Data

40 citations · 67 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 1 cited

Self-Supervised In-Domain Representation Learning for Remote Sensing Image Scene Classification

Ali Ghanbarzade, Hossein Soleimani

Transferring the ImageNet pre-trained weights to the various remote sensing tasks has produced acceptable results and reduced the need for labeled samples. However, the domain diff…

cs.CV2023

Supervised and Contrastive Self-Supervised In-Domain Representation Learning for Dense Prediction Problems in Remote Sensing

Ali Ghanbarzade, Hossein Soleimani

In recent years Convolutional neural networks (CNN) have made significant progress in computer vision. These advancements have been applied to other areas, such as remote sensing a…

stat.ML2015★ 40 cited

ATD: Anomalous Topic Discovery in High Dimensional Discrete Data

Hossein Soleimani, David J. Miller

We propose an algorithm for detecting patterns exhibited by anomalous clusters in high dimensional discrete data. Unlike most anomaly detection (AD) methods, which detect individua…

cs.LG2014★ 26 cited

Parsimonious Topic Models with Salient Word Discovery

Hossein Soleimani, David J. Miller

We propose a parsimonious topic model for text corpora. In related models such as Latent Dirichlet Allocation (LDA), all words are modeled topic-specifically, even though many word…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.