Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence.
Since deep learning and machine learning tend to be used interchangeably, it’s worth noting the differences between the two. As mentioned above, both deep learning and machine learning are subfields of artificial intelligence, and deep learning is actually a sub-field of machine learning.
Aiactive using Artificial intelligence and Machine Learning in Software for examples :
Automatic License Plate Recognition.
Make, Model and Colour Recognition.
Deep learning :
- The way in which deep learning and machine learning differ is in how each algorithm learns. Deep learning automates much of the feature extraction piece of the process, eliminating some of the manual human intervention required and enabling the use of larger data sets. You can think of deep learning as "scalable machine learning. Classical, or "non-deep", machine learning is more dependent on human intervention to learn. Human experts determine the hierarchy of features to understand the differences between data inputs, usually requiring more structured data to learn.
- "Deep" machine learning can leverage labeled datasets, also known as supervised learning, to inform its algorithm, but it doesn’t necessarily require a labeled dataset. It can ingest unstructured data in its raw form (e.g. images), and it can automatically determine the hierarchy of features which distinguish different categories of data from one another. Unlike machine learning, it doesn't require human intervention to process data, allowing us to scale machine learning in more interesting ways.
Automatic License Plate Recognition Engine:
- The highly advanced AI Active ALPR engine is available on PCs running Windows or Linux and can be connected to multiple cameras. The ALPR engine employs optical character recognition (OCR) technology to recognize license plates in real time on fast-moving traffic across several lanes simultaneously. This method is widespread around the world for law enforcement purposes, traffic control and vehicle tracking.
- Increase the traffic-handling capacity of an intersection.
- The engine supports multiple reporting options simultaneously and can be upgraded to perform high accuracy MMC (Make, Model and Color identification), VClass (Vehicle type classification), Country, Speed and direction in real time.
- The ALPR engine uses state-of-the-art state of the art object detection algorithms and computer vision techniques to provide high accuracy and performance in real time.
Make, Model and Colour Recognition:
- High accuracy Make, Model and Color (MMC) Recognition is now available in real-time. With a training database of over 165 makes. AI Active’s MMC can provide accurate data enabling traffic analytics.