It covers key features of targeted data for successful synthetic data creation and model training.
This is part 1, is this useful to y'all? Would you like more articles like this or on other topics from our experts?
As always, you can start creating your own synthetic data for free on Falcon. It's not Gen AI, its data crafted from digital scenarios, designed to align with a target domain.
It covers key features of targeted data for successful synthetic data creation and model training.
This is part 1, is this useful to y'all? Would you like more articles like this or on other topics from our experts?
As always, you can start creating your own synthetic data for free on Falcon. It's not Gen AI, its data crafted from digital scenarios, designed to align with a target domain.
The "as much data as possible" crew has been gaining on both posts lately, but intentional data is winning for both. We have a blog about creating targeted data, should I post it here on HF?
When you're looking for data, what's your focus (use the reactions below to vote): 🚀 Getting as many images as you can 🤯 Getting the right type of images (framing, domain, lighting, etc)
I know both are very important, but I'm curious what people would put as #1
NEW ARTICLE: "Detecting Beyond Sight: Building AI-Enabled SAR Intelligence with Synthetic Data"
Synthetic Aperture Radar (SAR) reveals what optical sensors can’t. AI can turn that information into actionable intelligence—but only with the right training data.
In our latest blog, we explore how Falcon’s new virtual SAR sensor solves the SAR data bottleneck for AI development. As the newest addition to Falcon’s sensor library, it models radar returns with precision—including azimuth, range resolution, signal intensity, and noise. This Falcon-specific, GPU-accelerated raytraced SAR model is exposed via Falcon’s Python API, giving teams precise, control over radar wave propagation and enabling physically grounded, highly customizable, and user-friendly SAR simulation.
The result? High-fidelity, automatically labeled synthetic SAR imagery from any scenario—on demand. No custom setup. No external workflows. Just mission-ready data for building AI models across defense, disaster response, agriculture, intelligence, and beyond.
NEW ARTICLE: "Detecting Beyond Sight: Building AI-Enabled SAR Intelligence with Synthetic Data"
Synthetic Aperture Radar (SAR) reveals what optical sensors can’t. AI can turn that information into actionable intelligence—but only with the right training data.
In our latest blog, we explore how Falcon’s new virtual SAR sensor solves the SAR data bottleneck for AI development. As the newest addition to Falcon’s sensor library, it models radar returns with precision—including azimuth, range resolution, signal intensity, and noise. This Falcon-specific, GPU-accelerated raytraced SAR model is exposed via Falcon’s Python API, giving teams precise, control over radar wave propagation and enabling physically grounded, highly customizable, and user-friendly SAR simulation.
The result? High-fidelity, automatically labeled synthetic SAR imagery from any scenario—on demand. No custom setup. No external workflows. Just mission-ready data for building AI models across defense, disaster response, agriculture, intelligence, and beyond.
Excuse the lag, it's from the real-time inference from the webcam đź‘€ . Did you know that YOLOv11 added Streamlit for live object detection straight from your webcam?
Excuse the lag, it's from the real-time inference from the webcam đź‘€ . Did you know that YOLOv11 added Streamlit for live object detection straight from your webcam?