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Name: Jonathan Müller

Type: User

Company: Bosch AI

Bio: Working on self-guidance in AI and semantic segmentation. Contributor to many open-source projects. Living the AI dream. 🌍

Location: Berlin, Germany

Jonathan Müller's Projects

dreamlens-segmentation-tensorflow

The repository comprises of various semantic segmentation networks designed using tensorflow for tasks like brain tumor segmentation. Additional contribution required for enhancement.

dreamlens-superpixelsegmentation-solution

Optimized solution to segment an image into super pixels using graph-based image segmentation algorithm. Ideal for computer vision applications.

dreamy-yolov5

This is a Go implementation of the YOLO V5 object detection system, enhancing its functionality and robustness.

python-braintumorsegmentation-enhanced

Enhanced brain tumor segmentation using advanced image processing techniques in Python.

semantic-segmentation-adapnet

This repository houses the TensorFlow model for the AdapNet training. AdapNet is used for semantic segmentation, which is easily trainable on a single GPU and has a fast inference time.

Implementation of Affinity Space Adaptation for Semantic Segmentation Across Domains. Includes code, trained models, and usage instructions. The implementation aims at addressing the problem of unsupervised domain adaptation in semantic segmentation, achieving state-of-the-art performance on standard benchmarks.

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