# Mustafa Chasmai

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/mustafa-chasmai/

## Facts

| Field | Value |
| --- | --- |
| Citations | 118 |
| Field | Domain Adaptation and Few-Shot Learning |
| h-index | 5 |
| i10-index | 3 |
| OpenAlex ID | https://openalex.org/A5027205312 |
| ORCID iD | 0000-0001-8694-3453 |
| Works | 19 |

## Researcher papers

- [A View Independent Classification Framework for Yoga Postures](https://scholariq.org/papers/a-view-independent-classification-framework-for-yoga-postures/)
- [From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments](https://scholariq.org/papers/from-forks-to-forceps-a-new-framework-for-instance-segmentation-of-surgical-2/)
- [Robust Prototypical Few-Shot Organ Segmentation With Regularized Neural-ODEs](https://scholariq.org/papers/robust-prototypical-few-shot-organ-segmentation-with-regularized-neural-odes/)
- [Adversarially Robust Prototypical Few-Shot Segmentation with Neural-ODEs](https://scholariq.org/papers/adversarially-robust-prototypical-few-shot-segmentation-with-neural-odes/)
- [PyKale](https://scholariq.org/papers/pykale/)
- [The iNaturalist Sounds Dataset](https://scholariq.org/papers/the-inaturalist-sounds-dataset/)
- [Representation Learning Using Rank Loss for Robust Neurosurgical Skills Evaluation](https://scholariq.org/papers/representation-learning-using-rank-loss-for-robust-neurosurgical-skills/)
- [A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation](https://scholariq.org/papers/a-language-guided-benchmark-for-weakly-supervised-open-vocabulary-semantic/)
- [From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments](https://scholariq.org/papers/from-forks-to-forceps-a-new-framework-for-instance-segmentation-of-surgical/)
- [Weakly Supervised Few-Shot and Zero-Shot Semantic Segmentation with Mean Instance Aware Prompt Learning](https://scholariq.org/papers/weakly-supervised-few-shot-and-zero-shot-semantic-segmentation-with-mean/)

## Researcher topics

- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)
- [Music and Audio Processing](https://scholariq.org/topics/music-and-audio-processing/)
- [Multimodal Machine Learning Applications](https://scholariq.org/topics/multimodal-machine-learning-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.