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M. Fathy

22 papers hereh-index 367.6k citations335 works total

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

author position
  • middle author13
  • last author7

Across the 20 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.AR3
  • cs.DC3
  • cs.NI2
  • eess.IV2
  • cs.PF1
same name
  • M. Fathy — 1 paper, h 5

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
20102023
most citedSTFCN: Spatio-Temporal FCN for Semantic Video Segmentation

49 citations · 166 across the 18 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CV2018★ 9 cited

Online Signature Verification using Deep Representation: A new Descriptor

Mohammad Hajizadeh Saffar, Mohsen Fayyaz, Mohammad Sabokrou +1

This paper presents an accurate method for verifying online signatures. The main difficulty of signature verification come from: (1) Lacking enough training samples (2) The methods…

cs.CV2018★ 6 cited

Semantic Video Segmentation: A Review on Recent Approaches

Mohammad Hajizadeh Saffar, Mohsen Fayyaz, Mohammad Sabokrou +1

This paper gives an overview on semantic segmentation consists of an explanation of this field, it's status and relation with other vision fundamental tasks, different datasets and…

cs.CV2018

AVID: Adversarial Visual Irregularity Detection

Mohammad Sabokrou, Masoud Pourreza, Mohsen Fayyaz +4

Real-time detection of irregularities in visual data is very invaluable and useful in many prospective applications including surveillance, patient monitoring systems, etc. With th…

cs.CV2018

Adversarially Learned One-Class Classifier for Novelty Detection

Mohammad Sabokrou, Mohammad Khalooei, Mahmood Fathy +1

Novelty detection is the process of identifying the observation(s) that differ in some respect from the training observations (the target class). In reality, the novelty class is o…

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