Senior Machine Learning Developer
- Verfügbarkeit einsehen
- 0 Referenzen
- 55€/Stunde
- 10290 Zapresic
- auf Anfrage
- hr | en
- 23.02.2024
Kurzvorstellung
Qualifikationen
Projekt‐ & Berufserfahrung
12/2023 – 12/2023
Tätigkeitsbeschreibung- Develop state of the art darts detection algorithm based on heuristic approach on limited hardware while keeping the accuracy very high.
Eingesetzte QualifikationenOpencv
12/2020 – 12/2023
Tätigkeitsbeschreibung
- Developed light sword and sun glare neural network-based detectors.
- Created a small and efficient yet accurate deep-learning light source-detector.
- Created a new and improved light source classifier.
- Finished large-scale codebase handover successfully.
- Managed the annotation process with the supplier and defined a new generation annotation structure for the light source mission.
- Worked on next-generation advanced driver-assistance systems.
C++, Maschinelles Lernen, Objekterkennung, Opencv
12/2020 – 12/2022
Tätigkeitsbeschreibung
A custom object detector in a very specific environment and I was in charge of the process that involved the object detector model, including data gathering, setting up an annotation pipeline, managing the annotation process, developing the model, and exporting the model to the iOS app.
The client didn't have any data whatsoever. The first step was data scraping and data selection. Considering the data scraping was from Google images, there were many duplicates in the dataset. I created a small annotation tool to remove duplicates, then I defined annotation instructions and set up the annotation process. I led a team of three annotators. The model development and export to the iOS platform were the final steps.
What was particularly interesting was the timeline. The project lasted for two and a half months and was successfully delivered and well received on the demo with the end client.
Data Science, Objekterkennung
12/2019 – 12/2020
Tätigkeitsbeschreibung
- Developed a depth estimation neural network with stereo video input in TensorFlow. This project included research and development of multiple state-of-the-art architectures, from Monodepth2, Struct2depth, Fast Deep Stereo to RobustMonoDE, and more.
- Created the annotation web tool in Dash/Flask, used for depth annotations.
- Implemented the neural network pipeline described in Fast Deep Stereo with 2D Convolutional Processing of cost signatures paper using TensorFlow and OpenCV.
Bilderkennung, Bildverarbeitung, Maschinelles Lernen, Opencv
12/2014 – 12/2019
Tätigkeitsbeschreibung
- Developed an accurate and robust ID-1 card detector neural network that works in real-time on mobile phones, developed using TensorFlow and OpenCV.
- Developed an extremely small and accurate TensorFlow implementation of the neural network for card analysis, used for immediate user feedback.
- Built an annotation tool for detecting blur in Dash/Flask, participated in the annotation process, and developed a robust neural network classifier in TensorFlow.
- Explored and developed a face action recognizer using TensorFlow and a Visage Technologies face detector.
- Researched a Croatian ID card verification through detecting hologram using Caffe for training, and Python, OpenCV, and GIMP for data augmentation.
- Created a plugin interface in the cfSuite desktop application in C++.
Developed custom plugin creator in C++ used for the desktop cfSuite application.
- Automated application testing procedures, used for finding bugs after updates.
Deeplearning4j, Opencv
Ausbildung
University of Zagreb Faculty of Electrical Engineering and Computing
Zagreb
Über mich
Weitere Kenntnisse
Machine Learning
Computer Vision
Deep Learning
OpenCV
Data Scraping
AWS
... and more
Persönliche Daten
- Kroatisch (Muttersprache)
- Englisch (Fließend)
- Europäische Union
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