Jihad Bourassi Email & Phone Number

Orléans, Centre-Val De Loire, France

Rabat, Rabat - Salé - Kénitra, Maroc

- Predicting Moroccan soil properties from hyperspectral images using Artificial Intelligence:1- Development of a desktop app for Hyperspectral Data Collection (C++,Qt,Opencv,Specim)2- Training and validation of a deep neural network models to predict the soil properties from the Collected Hyperspectral data using CNNs (Tensorflow, Keras,Python,Numpy,Pandas)3- Drafting of a detailed feasibility study report containing the results of the study.- Access control application with face recognition, face mask classification and temperature reading from thermal camera:1- Development of convolutional neural network for face detection (Tensorflow, Keras,Python,Opencv)2- Implementation of a tracking module for id assignment for each blob (Opencv)3- Training and validation of convolutional neural network for face mask classification (Tensorflow, Keras,Python,opencv)4- Development of KNN model for face recognition from the database of employees (Opencv, Scikit-learn)5- Development of a desktop app for for access control of employees (C++Qt,Opencv)- AI powered agricultural drone for beet cultivation:1- Data collection of beet fields images using a drone during different stages of growths (early stages, and advanced stages)2- Development of an annotation tool for the drone images collected of the beet fields (Python,Qt,Opencv)3- Image annotation using a semi-automatic annotation system into three classes beet plants, monocotyledonous weeds and dicotyledonous weeds4- Training and validation of a beet and weed plant segmentation/detection algorithm using Yolo and Yolact for the advanced stage and an NDVI vegetation segmentation + blob detection for the early stage of growth5- Training and validation of a classification model of monocotyledonous weeds and dicotyledonous weeds and the generation of geo-tagged maps with the position of the different types of weeds for the drone to access

Maroc

- Processing data from companies' balance sheets and developing default scores, solvency scores and maximum credit using Machine Learning algorithms.- Development of a national study on the Payment deadline using Data Clustering (k-means) to eliminate outliers.- Recommendation system of clients to prospect from a client portfolio (ACP, autoencoder, k-means, knn).

Préfecture De Casablanca, Morocco

Implementation of a system of automatic reading of Moroccan license plates and detection of similarity between images with Deep Learning and Machine Learning using Tensorflow, Keras,Opencv, Python and Django.

Diplôme D'Ingénieur, Data Science

Concour National Commun, Ingénierie, Admis Sans Oral

Baccalauréat, Science Math, Mention Bien