M
E
N
U
Transfer learning (TL) is a method in machine learning. It involves reusing “knowledge” that a model has acquired while being trained to address a specific problem (A) to address a second, similar problem (B). The ability to use experience to address new problems is innate to the human condition. When applied to deep learning, transfer
Image annotation is a method of adding captions to images. It has emerged as an essential mode of communication in the digital era. Image annotation has many use cases in the modern-day workplace. There are ten types of image annotation and their use cases, which will be discussed in detail on this page under the
Image annotation is integral to machine learning and artificial intelligence, especially when using computer vision (CV) models. It is the process where images of a particular dataset are labeled to help train a machine learning model. Different image annotation techniques such as polygon annotations and bounding boxes can do this. The benefits and importance of
Companies that rely on internal teams or automation to annotate data often find it difficult to manage increasing workloads and yet assure the same quality, speed, and security. Automation is the first casualty in such instances. Why? A lot of time is spent on perfecting algorithmic models to accurately match complex behavioral patterns and make