technology Meta Releases SAM & It's Going To Change Data Labeling Segmentation, the process of extracting relevant parts of an image, is a crucial but complex task that has many practical applications. For example, in cameras, segmentation is used to create beautiful portrait mode shots, which differentiate between the foreground (object of interest) and the background using segmentation. However, creating applications
data annotation 10 Computer Vision platforms for Data-centric AI Computer vision is a rapidly growing field of artificial intelligence that allows machines to interpret and understand visual information from the world around them. With the explosion of image and video data, computer vision has become increasingly important in a wide range of industries, including healthcare, automotive, retail, and more.
Business The Role Of AI In Workflow Automation Platforms In today's world, where businesses strive to be more efficient and productive, workflow automation has become increasingly popular. Workflow automation platforms help organizations automate routine tasks, streamline workflows, and improve overall efficiency. However, with the advent of artificial intelligence (AI), these platforms have taken a significant leap forward
data annotation 6 Ways AI-Assisted Data Labeling Tools Help Faster Development? Data labeling is a crucial step in machine learning and artificial intelligence that involves annotating data to train algorithms. However, the process of data labeling can be time-consuming, expensive, and prone to errors when done manually. That's where AI-powered data labeling platforms come in, which are revolutionizing the
data annotation Automation in Data Labeling Platforms: A Comprehensive Guide Data labeling is an essential process in training machine learning models, and it involves manually annotating large datasets to provide accurate and consistent labels for use in the training process. However, the manual process of data labeling can be time-consuming, error-prone, and expensive. That's where automation comes into
data annotation 8 Industries Solving Problems Using Image Annotation Image annotation is a crucial task in the field of computer vision that involves adding metadata to an image. With the help of image annotation, computers can understand and interpret the contents of images, making it possible to automate various tasks that were previously only possible for humans. In this
data annotation 10 Data Labeling Platform for Automated Data Annotation Data labeling is an essential process in machine learning and artificial intelligence that involves the tagging, classification, and annotation of data. However, manual data labeling can be time-consuming and expensive, which has led to the development of automated data labeling platforms. These platforms use various techniques such as computer vision
SDG 12 Examples Of How AI Can Help In Education Education has always been a cornerstone of human civilization, helping to determine the course of both the futures of individuals and entire communities. Traditional Educational models, on the other hand, are finding it difficult to keep up with the rate of change as the world continues to evolve and become
Product Feature Update How model-assisted image labeling helps teams for faster AI? In recent years, artificial intelligence (AI) has become increasingly popular, and its potential applications have multiplied rapidly. One of the main components of AI is machine learning (ML), which involves training models to recognize patterns in data and make predictions based on those patterns. One of the most important tasks
case study How Perceptly Uses Image Similarity To Fasten Up Annotation Perceptly helps Ad agencies to analyze the real reason of what and why their creatives worked or not. Its creative optimization engine identifies messaging, visual and copy elements that are driving performance. They basically aim at providing personalized report insights from ads. They help in letting its customers know how
News Amazon Tests Self-Driving Robotaxi with Employees Onboard Are you ready for the future of transportation? Be prepared because Amazon's self-driving robotaxi is now accessible! By using its own employees to operate its self-driving robotaxi on public roads, Amazon is bringing us one step closer to a world with driverless cars. Because of the power of
technology Supervised vs. Unsupervised Learning: Choosing the Right Path for Your Data Analysis Supervised learning uses labeled data for predictive tasks like spam filtering or credit scoring, while unsupervised learning explores unlabeled data to identify patterns, aiding applications such as customer segmentation and anomaly detection
dataset Maximizing Data Ingestion Performance for High-Volume Data Sources In 2020, 64 zettabytes of data were generated in total! According to estimates, this amount will climb to 180 zettabytes by 2025 as the number of individuals working from home increases. With important system sources like smartphones, power grids, stock markets, and healthcare integrating more data sources as storage capacity
technology Labellerr: A self-hosted & secured data annotation platform In the world of data science, efficient and accurate labeling of data is crucial to ensuring successful Machine Learning applications. While an array of online tools exist to make data labeling easier, they often involve managing multiple vendor relationships, hosting external datasets on an alien server environment with limited accessibilities,
technology Leveraging YOLO Object Detection for Accurate and Efficient Visual Recognition It’s become increasingly evident that the YOLO algorithm has revolutionized the way we think about algorithms, and is quickly becoming an essential tool for machine learning applications. By streamlining object detection through efficient deep neural networks, YOLO has shown us how powerful one can be when effectively leveraging both
technology Data annotation outsourcing: A step-by-step guide Are you working with image-based data and struggling to keep up with the workload? Image annotation is an important part of any machine learning project that deals with image or video data, helping to speed the model development process. Unfortunately, not everyone has the technical skills or time needed for
data annotation The next big thing in data annotation Data enthusiasts use a variety of datasets while creating ML models, carefully adjusting each one to the model's training needs. Robots can therefore recognize content that has been labelled in a wide range of understandable formats, including images, texts, and videos. In order to train their algorithms to
Watch out for these features in a video annotation tool When it comes to making the most of video-based learning, there is no better tool than an efficient and user-friendly annotation system. With the right annotation tools, you can improve engagement with your videos by boosting their interactivity and intelligently segmenting content for quick retrieval. Furthermore, you can easily add
data annotation How to super fast data annotations process with automation? Lexi is a US-based data scientist and she is currently working on a data annotation project. She is looking for various methods to bring automation to data annotations. Let’s see what are the possible options for her. Data annotation is a critical process for capturing data that can provide
Product Feature Update Automating your image segmentation annotation with Labellerr Image segmentation annotation is an essential part of the machine learning pipeline, yet it can be time-consuming and requires specialized expertise and repetition. Fortunately, there are now powerful tools available to automate this step, such as Labellerr. With this software, you can easily create feature masks from your images to
Product Feature Update Automating object detection AI development with Labellerr If you're a data scientist working in the AI and machine learning space, then you know how time-consuming it can be to label datasets manually. This process is critical for training object detection algorithms, but automation becomes essential with traditional methods of labeling datasets, often taking days or
technology What Is Image Enhancement & Its Effect On Machine Vision Imagine trying to drive a car in dense fog. Your visibility is limited, making it hard to see what's ahead. Now, picture someone handing you a pair of glasses that cut through the fog, suddenly revealing the road and obstacles clearly. This is what image enhancement does in
technology How Dall-E and stable diffusion will automate our work in future? The further adoption of both AI and automation technologies has been on the rise over several years, with more organizations looking to use automated systems as a way to improve efficiency, reduce costs and increase accuracy. This also means that we should take time to look at recent advances in
technology Understand the tech: Stable diffusion vs GPT-3 vs Dall-E The world of Artificial Intelligence (AI) is rapidly innovating with the development of new algorithms, models, and techniques. But how do you decide which AI technology to use? To help you in that decision-making process, we'll look at the differences between two of today's popular AI
data annotation Image Annotation Techniques - A Complete Guide For Training An AI Model Many artificial intelligence (AI) products and services that we employ on a daily basis are built around image annotation. Additionally, it is among the most significant activities in the process of creating training data for Computer Vision (CV) technologies. Annotators utilize tags or metadata to identify the features of data
