Daniel Alejandro Martelliti

Developer and supporter of ML/DL models and implementation design into the project. Models about classifiers, object detection, face tracking, movement detection, face recognition, and tools to search duplicate faces quickly. Knowledge: Artificial intelligence, Multimodal, Object Detection (SSD). Data Science. Computer vision. OCR, and signal processing. BackEnd. Technologies: Tensorflow, OpenCV, sklearn, skimage, SciPy, Pandas, Mxnet, KNN, SVM, Linux, AWS, Redis, Docker, Git, Jupyter, Colab, PostgreSQL.

Generation of CNN and RNN Models on several health and identity branch projects running on a platform of doctors online. Implementation of real-time algorithms on a WPA platform in React. Developer and contributor of microservices (Backend). Knowledge: Google Cloud, AWS, BigData, Health, Identity, and Fraud Images. GPU/TPU, Fourier Fast Transform. Technologies: Python, Tensorflow, OpenCV, sklearn, skimage, SciPy, Pandas, Linux, Firebase, Redis, Docker, Git, Jupyter, Mxnet.

Developments of algorithms and platforms using image digital processing. Counter corn plans and predictor maturity soybean achieving (image digital processing). Segmentation (Machine Learning and image digital processing). Developer and contributor of microservices. Knowledge: GeoSpatial Images, Big Data - AWS - Cloud Computing Services, Multiprocessing and multi-threading. GeoSpatial Images. Technologies: Python, Linux, Amazon Web Services, Git, Jupyter. Pandas, Scipy, OpenCV, Sklearn, KNN, GDAL, Shapely.

The published paper is as follows (XLIII CLEI - 46 JAIIO): DyCEI Development algorithms and platforms using image digital processing. (Data Science) Segmentation and Clustering (Machine Learning). Knowledge: GeoSpatial and Satellite Images, MODIS. Rasters and Shapes. Delaunay Technologies: QGIS, ArcGIS, Python, Linux, Git, Jupyter. Pandas, Scipy, OpenCV, Sklearn, GDAL, Shapely, Fiona.