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20212025
most citedUsing Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation

15 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Prot2Token: A Unified Framework for Protein Modeling via Next-Token Prediction

Mahdi Pourmirzaei, Farzaneh Esmaili, Salhuldin Alqarghuli +6

The diverse nature of protein prediction tasks has traditionally necessitated specialized models, hindering the development of broadly applicable and computationally efficient Prot…

q-bio.QM2022★ 2 cited

A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Sites Prediction

Farzaneh Esmaili, Mahdi Pourmirzaei, Shahin Ramazi +2

Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and as a result, regulating diverse cellular processes in prokaryotic and e…

q-bio.QM2021

A Brief Review of Machine Learning Techniques for Protein Phosphorylation Sites Prediction

Farzaneh Esmaili, Mahdi Pourmirzaei, Shahin Ramazi +1

Post-translational modifications (PTMs) have vital roles in extending the functional diversity of proteins and as a result, regulating diverse cellular processes in prokaryotic and…

cs.CV2021★ 1 cited

How Self-Supervised Learning Can be Used for Fine-Grained Head Pose Estimation?

Mahdi Pourmirzaei, Farzaneh Esmaili, Ebrahim Mousavi +2

The cost of head pose labeling is the main challenge of improving the fine-grained Head Pose Estimation (HPE). Although Self-Supervised Learning (SSL) can be a solution to the lack…

cs.CV2021★ 15 cited

Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation

Mahdi Pourmirzaei, Gholam Ali Montazer, Farzaneh Esmaili

Facial emotion recognition (FER) is a fine-grained problem where the value of transfer learning is often assumed. We first quantify this assumption and show that, on AffectNet, tra…