🚀 New on Datature: t-SNE Embedding Visualization Turn thousands of image embeddings into an interactive 2D map - spot duplicates, detect anomalies, visualize clusters, and speed up curation. Now Live → Find it under “Projector” in your Asset Tab

At @DatatureAI, we are unifying multi-planar reconstruction annotation, volumetric deep learning, and seamless deployment into a single, integrated intelligence layer. ⚡ Advanced Annotation – AI-driven, scalable labeling for CT, MRI, PET, with strict consensus/review enforcement. ⚡ Volumetric Model Training – Expanded #3DUNET architectures, fine-tuned with 3D augmentation for unparalleled precision. ⚡ Seamless Deployment – Native #3DSlicer integration & PACS support to operationalize insights at scale. This is just the beginning.

Exciting news! @DatatureAI is headed to #MDMWest in Anaheim, Feb 4-6 at the Anaheim Convention Center, Booth #5529. Discover cutting-edge machine learning and computer vision for medical, manufacturing & materials solutions with live demos!

Learn how to train an object detection model with YOLOv8 on Datature’s Nexus platform. In this tutorial, Leonard walks you through: - Training a model to identify and locate objects within images. - Optimizing workflows for speed and accuracy. Applications include warehouse management, autonomous vehicles, and retail analytics. Watch now and see how Nexus simplifies complex tasks #ObjectDetection #AI #ComputerVision #Datature #DatatureTutorials #YOLOv8

Learn how to train a video classification model using MoviNet on Datature’s Nexus platform. youtu.be/QXIavCwMzoY In this tutorial, Leonard guides you through: Training a model to analyze and classify actions or events in video sequences. Enhancing workflows for real-time video processing and accuracy. Applications include sports analytics, surveillance systems, and content moderation. Watch now and explore how Nexus simplifies advanced video analysis. #VideoClassification #AI #ComputerVision #Datature #DatatureTutorials #MoviNet

Learn how to train a keypoint estimation model using YOLOv8 on Datature’s Nexus platform. youtu.be/u1_AfU15eHs In our latest tutorial, Leonard walks you through: - Training a model to detect key points of interest in an image. - Optimizing workflows for precision and speed. Applications include human pose estimation, gesture recognition, and sports performance analysis. Watch now and see how Nexus simplifies complex tasks! #KeypointEstimation #AI #ComputerVision #Datature #DatatureTutorials #YOLOv8

SAM-2 revolutionized video object segmentation with its memory-based architecture for sequential frames. However, challenges like occlusions and error propagation remain. Derivative models like SAMURAI and SAM2Long tackle these issues with advanced memory and motion-aware features, enhancing accuracy and long-term tracking. Discover how they overcome SAM-2's limits: datature.io/blog/beyond-sam-…

Learn how to build a semantic segmentation model using DeepLab V3 on Datature’s Nexus platform buff.ly/3Dlrg8G In the first tutorial of our series, Leonard walks you through: - Training a model for pixel-perfect object segmentation. - Streamlining workflows for faster, accurate results. Use cases include defect detection in manufacturing, autonomous driving, and medical imaging. Watch now and see how Nexus simplifies complex tasks here: #SemanticSegmentation #AI #ComputerVision #Datature #DatatureTutorials #DeepLab

Dive into our latest tutorial where we walk you through the fundamentals of training a cutting-edge #keypoint estimation model 🧠 From identifying key points in images to analyzing skeletal structures in videos, this concise 8-minute guide will equip you with the knowledge to create your next #computervision or skeleton detection model.

Playlist - youtube.com/watch?v=p1p3O91I…

Thrilled to showcase our technology at #FIRAUSA, marking our debut at this premier agriculture event. This morning, we spoke with visionary roboticists and forward-thinking farmers exploring machine vision solutions for their next #AgTech initiatives. Visit us at Booth D7! 👋

With Low Confidence Sampling, users can easily identify and prioritize misclassified or uncertain predictions, optimizing labeling and fine-tuning efforts.

Datature is excited to announce our latest integration of Segment Anything Model 2.0 into our Annotator Platform ✨ This update will enable all our users to label video datasets 10x faster with fewer clicks and error corrections. Check out some of our other SAM-2 updates in our blog 👇 datature.io/blog/annotate-im…

Datature is excited to unveil the latest support for Vision Transformers (ViT) into our Nexus platform, propelling forward the capabilities of segmentation tasks with cutting-edge technology. ViTs leverage self-attention mechanisms, which allow them to focus on different parts of an image and understand contextual relationships better than conventional convolutional neural networks (CNNs). This approach improves the model’s ability to handle complex, high-resolution images, enhancing accuracy in critical applications such as medical imaging and defect detection. Today, teams can now fine-tune #transformers on their dataset today on Datature Nexus 🌟 Read The Guide 👉datature.io/blog/introducing…

Datature is excited to present our detailed overview of MoViNet, a state-of-the-art architecture for efficient video classification, now fully integrated into our platform. MoViNet is designed for significant computational and memory efficiency advantages by incorporating advanced 3D CNNs. This model has been adapted for video with 3D convolution layers to capture temporal information effectively. Whether you're engaged in #sportsanalytics, media processing, or #actionrecognition, this guide offers insights on how you can build your own video classification on Datature Nexus. Explore the full guide and take your video classification projects to the next level with Datature's robust tools and resources. 🌟 Read The Guide 👉 datature.io/blog/introducing…

Datature proudly supports @trendspek's mission to revolutionize asset management with its Precision Asset Intelligence 3D visualization software. Together, we've developed an advanced machine-learning pipeline for structural crack detection, enhancing Trendspek's software to identify and segment cracks efficiently. Trendspek's solutions speed up crack detection processes by more than five times, leveraging Datature's end-to-end #MLOps platform for swift custom crack model development and deployment. The collaboration showcases a significant innovation in 3D asset management, and we are excited about future possibilities in AI-powered inspection​ and Trendspek's innovation in this space ⚡️ datature.io/blog/trendspek-o…

Harnessing the analytical prowess of our integrated asset management, we're redefining the way you interact with your data - 🔎 Metadata Query: Unveil intricate data insights with logical queries, assign groups, and label tasks based on data lineages. Easily embed metadata into your assets with our Datature Python SDK (SubjectID, Camera Intrinsincs, Temperature, GeoInfo, and more) 🖼️ Similarity Search: Leverage cutting-edge #embeddings to identify related visuals, enhancing data curation swiftly. Datature enables teams to run similar image search across datasets (medical, manufacturing, satellite, etc) to ensure that teams can quickly arrange data for model training. Technical Blog - lnkd.in/gjEvyke9 Developer Docs - lnkd.in/gd-Km64r