AI, ML and Computer Vision Meetup - September 24, 2026

Join our virtual meetup on September 24 to hear talks from experts on cutting-edge topics across AI, ML, and computer vision.

At Mercedes-Benz, our AI Principles guide every step of innovation, emphasizing responsible use, safety and reliability, explainability, and the protection of privacy. These principles go beyond statements and actively shape how we design, test, and deploy AI systems in real-world automotive and enterprise settings.

In this talk, I will present how these principles inspired our recent research on when reusing LoRA (Low-Rank Adaptation) is effective. By combining theoretical analysis with synthetic data as a proxy for enterprise scenarios, we uncovered the strengths and limitations of modular AI components under constrained data access.

Our findings provide practical guidance on when reused LoRAs could deliver high-quality results.

This presentation provides a detailed workflow related to coffee yield estimation in a dense environment. With photos of pre-harvest coffee plants from a couple of coffee estates, details related to pre-processing, annotation to detect regions of interest (ROI), object detection training and inferencing results with various Yolo models and finally segmentation with SAM2 and Yolo*-seg with training and inference results to determine the count of raw, pre-mature, mature and over-mature coffee berries and finally the yield of the entire estate.

All this is based on real world data captured on iPhone and android phones.

Image collections are humans' primary way of capturing the world, yet advances in generative editing remain largely inapplicable to this modality. We address this gap by introducing Match-and-Fuse - a zero-shot, training-free method for consistent set-to-set generation from image collections that share a common visual element but differ in viewpoint, capture time, and surrounding content.

Our key idea is a unified graph-based framework that combines dense correspondences with an emergent prior in text-to-image diffusion models to generate coherent canvases. We achieve state-of-the-art consistency and visual quality, and unlock new creative capabilities for content generation.