Artificial Intelligence systems powered by deep learning are changing how we work, communicate, and make decisions. If we ...

How to Choose the Right Data Annotation Method for Autonomous Driving Applications When building fully autonomous (Level 5) vehicles, choosing the right method to label or "annotate" the data is a key ...

A recent article accepted for publication in Data in Brief introduced an image-type dataset for deep learning-based detection of building facade features. The data was prepared from the static ...

Also, coordinating big annotation projects can cause bottlenecks. Especially, when a project focuses on different types of data, and you need to make sure all annotations are accurate.

Large Data Requirements: Deep learning models require vast amounts of labeled data to achieve high accuracy. The more data the system has access to, the better it can learn complex patterns.

Learn More. Deep learning is a subset of machine learning that uses neural networks with multiple layers to model complicated patterns and representations in data.

Deep learning focuses on predicting or classifying data, while generative AI creates new content. (Jump to Section) Common deep learning techniques include CNNs, RNNs, and LSTMs. (Jump to Section) ...