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Parviz Ghaderi

Researcher at École Polytechnique Fédérale de Lausanne

Publications -  9
Citations -  208

Parviz Ghaderi is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: System identification & Support vector machine. The author has an hindex of 5, co-authored 7 publications receiving 115 citations. Previous affiliations of Parviz Ghaderi include Shahid Beheshti University & University of Isfahan.

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A community-based transcriptomics classification and nomenclature of neocortical cell types

Rafael Yuste, +71 more
- 24 Aug 2020 - 
TL;DR: This work proposes the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex that should be hierarchical and use a standardized nomenclature, and could serve as an example for cell type atlases in other parts of the body.
Journal ArticleDOI

Muscle Activity Map Reconstruction from High Density Surface EMG Signals With Missing Channels Using Image Inpainting and Surface Reconstruction Methods

TL;DR: The proposed reconstruction algorithms could be promising new tools for reconstructing muscle activity maps in real-time applications if proper reconstruction methods could recover the information of low-quality recorded channels in HDsEMG signals.
Journal ArticleDOI

Electrophysiological Profiling of Neocortical Neural Subtypes: A Semi-Supervised Method Applied to in vivo Whole-Cell Patch-Clamp Data.

TL;DR: A novel semi-supervised classification method based on waveform shape of neurons' spikes using in vivo whole-cell patch-clamp recordings is proposed, which is a promising new tool in recognizing cell's type with high accuracy in laboratories using in vitro/vitro whole- cell patch-Clamp recording technique.
Proceedings ArticleDOI

Hand kinematics estimation to control prosthetic devices: a nonlinear approach for simultaneous and proportional estimation of 15 DoFs

TL;DR: Generalized Regression Neural Network (GRNN), a non-linear system identification approach, is applied to estimate fingers kinematics (15 Degrees of Freedom) from sEMG signals to provide fast, accurate, and intuitive simultaneous and proportional control strategy for myoelectric hand prostheses.
Posted Content

A community-based transcriptomics classification and nomenclature of neocortical cell types.

TL;DR: In this paper, the authors adopt a transcriptome-based taxonomy of the cell types in the adult mammalian neocortex, which is configured to flexibly incorporate new data from multiple approaches, developmental stages and a growing number of species, enabling improvement and revision of the classification.