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Internship opportunity: generative data augmentation for improving spore detection model

Mons
Stage
Multitel asbl
Publiée le 18 novembre
Description de l'offre

Trans-e-Bio, a part of the Biocontrol 4.0 initiative will develop digital tools to support the adoption of biocontrol solutions in agriculture across the France-Wallonia-Flanders (FWV) border region. By integrating local risk detection and predictive models, the project helps farmers optimize treatment timing and reduce synthetic pesticide use. The A.I department from Multitel will design and build A.I algorithms for spore detection, recognition, and infection risk prediction. The objective of this internship is to improve model performance through advanced data augmentation. This will involve developing a state-of-the-art artificial intelligence approach for realistically simulating field-like conditions in microscopic images of spores. In practice, the intern will design and implement a generative model capable of learning the noise and contamination patterns (e.g., dust, pollen, debris, background artifacts) present in field-captured microscopic spore images, and synthetically overlaying these patterns onto clean, lab-grown spore images. The end goal is to produce augmented datasets that mimic real-world field conditions, thereby improving the robustness and generalization of machine learning models for spore detection and analysis. The performance of the implemented methods will be evaluated using reference datasets, and potential limitations and areas of improvement will be identified. Thus, the different stages of this internship are as follows: Literature review on existing data augmentation and generative modelling techniques. Selection of suitable augmentation strategies for the targeted use case(s). Familiarization with the relevant open-source languages and libraries (Python, PyTorch, OpenCV, etc.). Implementation of the selected generative and augmentation method(s). Performance evaluation using the reference dataset and relevant quantitative metrics. Algorithmic improvement based on experimental results and analysis. Writing of the internship report and presentation of the results. Expected qualifications: Skills in signal and image processing and machine/deep learning, knowledge of Python, analysis and synthesis skills, autonomy, proactivity, curiosity, English desired. An internship of 4 months duration CV and cover letter requested You will work in a dynamic and welcoming environment. You’ll be part of a friendly and energetic team. We offer a stimulating and supportive work environment. Recognized as a center of excellence at the international level, Multitel develops and integrates emerging technologies in the industrial sector. These technologies are focused on five main areas of activity: Networks and Cybersecurity, Applied Photonics, Artificial Intelligence, Embedded Systems, and Railway Certification Within the Artificial Intelligence department, the AI team holds a crucial role in supporting companies with their technological innovation projects, guiding them from the feasibility phase to the minimum viable product in various application fields such as aerospace, automotive, Smart Cities, Industry 4.0, medical sciences, defense, and more. We love fresh ideas, shared coffees, and motivated people. If you’re eager to learn fast and make a real impact, join us!

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