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Introducing Field Extraction: Automate Data Extraction at Scale
Eolas Medical Enhances Clinical Knowledge Access with Agentic Document Extraction
Agentic Document Extraction: Live Demo & the Steps You Need to Get Started
Auto-Fill Job Applications with Agentic Document Extraction
Introducing Field Extraction: Automate Data Extraction at Scale
Over the past four months, LandingAI’s Agentic Document Extraction tool has seen rapid adoption across industries. Motivated by this momentum, our team has been hard at work expanding the tool’s capabilities. We’re excited to introduce a major new feature: Field Extraction. What Is Field Extraction? Field Extraction enables you to extract structured data directly from […]
Eolas Medical Enhances Clinical Knowledge Access with Agentic Document Extraction
About the Customer Eolas Medical is a leading healthcare technology company dedicated to streamlining access to medical knowledge right at the point of care. Founded by Dr. Declan Kelly, an emergency medicine physician by background, Eolas translates to “knowledge” or “information” in Irish, reflecting the company’s mission to empower clinicians with rapid, reliable access to […]
Agentic Document Extraction: Live Demo & the Steps You Need to Get Started
In this webinar, learn about Agentic Document Extraction (ADE), an agentic vision technology that revolutionizes how you extract and process structured data from complex documents. Designed for developers, this webinar demonstrates how ADE leverages layout-aware parsing, visual grounding, and agentic workflows to deliver high-accuracy extraction—without the need for manual template configuration or model fine-tuning. What […]
Auto-Fill Job Applications with Agentic Document Extraction
I’m sure—like myself and millions of others—you’ve spent hours copying and pasting the same information into job applications 🥱🎯. In this tutorial, we’ll walk through how you can build a powerful automation tool that extracts key data from your resume and fills out LinkedIn job applications for you—automatically! Thanks to LLMs, “developer” is now a […]
LVMs enable enterprises to more quickly solve computer vision problems; LandingAI to help enterprises build and run LVMs at the edge, on-prem, and in the cloud Palo Alto, CA., December 4, 2023 — LandingAI, the leading computer vision cloud platform, announced the launch of its capability to help enterprises build domain-specific large vision models […]
LandingLens offers many options for uploading images to your projects, including the ability to upload pre-labeled images. If you have a Segmentation project, you can upload pre-labeled images by uploading them, their segmentation masks, and a defect map. Check out this tutorial video for more information.
You can create an AI snapshot of some or all of the images in your project at any time. A snapshot includes the selected images and their labels, metadata, tags, and labeling tasks. With these AI snapshots, you can quickly perform actions, like training a model using only the snapshot or creating new projects from […]
In LandingLens, you can apply tags to images. This lets you quickly perform an action, like creating labeling tasks or splits. See how this works by watching this tutorial video.
Empower Your Learning Journey and Elevate Your Skills with LandingLens Computer Vision Fundamentals LandingAI is thrilled to announce the launch of its first course: LandingLens Computer Vision Fundamentals! Our mission is to provide you with insightful, engaging, and informative content that will empower you to grow and achieve your goals. Whether you’re new to LandingLens […]
Check out our presentation at the upcoming “Artificial Intelligence and Machine Learning for Manufacturing” virtual conference, hosted by NAFEMS. We are teaming up with NXP to discuss “Leveraging Data-Centric AI in Automatic Defect Classification (ADC) for Outgoing Quality Inspection in Semiconductors”.
Check out the latest updates from LandingAI in November 2023, including the exciting launch of our Computer Vision Fundamentals course.
LandingAI offers a feature to deploy LandingLens models using Docker. To deploy models using a Docker Instance, you must first install the LandingAI Docker Image. Check out this tutorial video to see how to do that.
LandingAI offers a feature to deploy LandingLens models using Docker, enabling DevOps users to manage model inference programmatically. This tutorial video shows you how to launch a Docker instance. Here are some pre-requisites that you need before you can run the command to launch a Docker instance: – License key – API key – Model […]
New deployment choice gives LandingAI users new option to deploy at scale
Estimate How Many Sips of Coffee You Take In this tutorial, we are going to use a computer vision deep learning model trained in LandingLens to create a simple coffee mug detector using our computer webcam, so we can count how many times we sip coffee while working. As an end-to-end platform, LandingLens offers its […]
Kitting is a crucial factor in the efficiency and organization of manufacturing assembly lines. It’s a common process in discrete manufacturing and involves packaging all the items needed to ship a product to customers. For many product lines, this step is often the last opportunity to ensure that products leaving the factory are high quality, […]
There are several ways to upload images into LandingLens, the Visual AI platform from LandingAI. Watch this video to learn how to upload a labeled Object Detection dataset into a LandingLens project. LandingLens supports uploading labeled Object Detection datasets in the Pascal VOC format. We provide Helper Scripts to convert COCO and YOLO datasets […]
LandingLens automatically splits images into the Train, Dev, and Test sets during model training. However, if you want to split images into datasets manually, LandingLens offers multiple ways to do this. Watch this tutorial video to learn more! Note: If you’re unfamiliar with the concept of splits, check out this video to learn more.
Having the Train, Dev, and Test sets are an essential part of building any machine learning model. In LandingLens, images are automatically split into these datasets. If you’re curious about how the Train, Dev, and Test sets work, then this video is for you!
Did you know you can run inference in LandingEdge by pulling frames (stills) from a video? This is just one of the many options for running inference in LandingEdge. Check out this tutorial video to find out how.
Did you know you can run inference in LandingEdge by calling an API? This is just one of the many options for running inference in LandingEdge. Check out this tutorial video to find out how.
You’ve probably heard of artificial intelligence (AI) and computer vision (CV), but have you ever wondered what these concepts are and how they work together? Check out this video to learn more.
Did you know you can run inference in LandingEdge by dragging and dropping images to a folder? This is just one of the many options for running inference in LandingEdge. Check out this tutorial video to find out how.
LandingLens has a built-in feature that lets you test how a trained model might behave in an actual deployment. Check out this tutorial video on our AI prediction models to see how it works.
This video demo, led by Landing AI Solutions Engineer David Park, focuses on metal casting and using computer vision for defect detection. The session highlights how LandingLens, Landing AI’s end-to-end platform, can classify and detect defects in metal-casted parts like submersible pump impellers and steel discs. Park provides an overview of the platform’s capabilities, […]
In LandingLens, after you’ve uploaded and labeled your images, you can train your deep learning model online. Learn how to use the default Train method, where LandingLens will automatically fine-tune its settings to optimize speed and model accuracy in this tutorial video.
Palo Alto, CA., September 26, 2023 — Landing AI, the leading computer vision cloud platform, announced the launch of the Landing AI App Space, a new repository of applications and use cases to help developers more quickly create their own customized Landing AI-based computer vision solutions. The App Space will share sample mobile friendly models […]
Learn how to build user-friendly AI applications using LandingLens and Streamlit. Discover the secrets to creating powerful and intuitive AI apps.
Easily create and use an AI cell colony counting app on your mobile device with Landing AI's innovative tools. Learn more about LandingLens here!
Explore the future of quality control with our Printed Circuit Boards (PCBs) Component Detection App. Try our sample mobile app or build your own QR app here.
When you create a project in LandingLens, it is visible to all users in your instance of LandingLens. You can make projects private anytime and invite only specific members to access them. Check out this tutorial video to learn how to do this.
In the latest version of LandingEdge, you can assign a graphics processing unit (GPU) to an inspection point. Running an inspection point on a GPU is faster than running on a central processing unit (CPU). Check out this tutorial video to learn how to assign a specific GPU to an inspection point in LandingEdge.
LandingAI’s latest version of LandingEdge offers roles to limit who can access different parts of the system. This is useful if LandingEdge is deployed to a shared machine and you want to prevent users from accidentally stopping or changing an inspection point. Check out this tutorial video to learn more about how to manage these […]