Dr Arnaud Nguembang Fadja



Beruf: Head of Machine Learning

Research Department, Paragon semvox GmbH

Paragon semvox GmbH

Konrad-Zuse-Str. 19, D-66459 Limbach (Saarland), Germany

Tel: +49 (0) 6841 80 90 10 Fax: +49 (0) 6841 80 90 10

E-Mail: arnaud.fadja.n@gmail.com

Paragon semvox GmbH

Dr Arnaud Nguembang Fadja

BETREUUNG DER ABSCHLUSSARBEIT

MASTER-ABSCHLÜSSE

2023

Intelligent Fruit Inspection System: Developing a YOLO-based Model for Identifying Defects on Plums Surface. [.pdf]

2023

Towards an empathic driving assistant: Explainable emotion recognition from driving context [.pdf]

2023

Selected Medicinal Plants Leaves Identification: A Computer Vision Approach [.pdf]

2022

Computer Vision for Segmentation and Quantification of Damage Surfaces on African Plum Fruits [.pdf]

2018

Runtime configurable deep neural networks for power-efficient adaptive architectures [.pdf]

BACHELOR-ABSCHLÜSSE

2024

Design and Implementation of Customised Widgets Widgets for Data Management in an E-learning Platform [.pdf]

2024

Web interface for managing permissions in a E-learning platform for high schools [.pdf]

2024

Development of a course management api for an educational platform based on ruby on rails [.pdf]

2024

Web interface for managing school fees in an E-learning environment for high schools [.pdf]

2024

Implementation of a web interface for the evaluation of teaching activities and infrastructures in a high school e-learning platform [.pdf]

2024

E-learning platform for high schools: responsive interface for web tables on mobile devices [.pdf]

2023

Ruby on Rails API for digitising school fees in secondary schools [.pdf]

2019

Convolutional Neural Networks for classification of genetic data [.pdf]

2019

Analysis of genetic data using Convolutional Neural Networks [.pdf]

2019

Application of Recurrent Neural Networks (RNN) for text classification of mathematical games” [.pdf]

2017

CREATION OF A DEEP LEARNING DEMONSTRATION WEBSITE [.pdf]

2017

Development of an Image Classification System based on Convolutional Neural Networks [.pdf]

2017

Deep Learning Fundamentals: Building a sample website [.pdf]

2017

Image classification with deep learning [.pdf]