4 posts tagged with "Machine Learning"

Human face emotion classification is the process of identifying and categorizing emotions in human expressions, human speech, or text. This can be done through various techniques, such as natural language processing, machine learning, and sentiment analysis. The goal of emotion classification is to understand and interpret human emotions in order to improve communication, decision-making, and overall emotional intelligence. Common emotions that are classified include happiness, sadness, anger, fear, surprise, and neutral.

Computer vision is a field of artificial intelligence that focuses on teaching computers to interpret and understand visual data from the world around them, such as images and videos.

In manufacturing, computer vision can be used to automate a variety of tasks, such as quality control and inspection. For example, a manufacturing company could use computer vision to automatically inspect products for defects or to monitor production processes to ensure they are running smoothly. This can help to improve the efficiency and accuracy of the manufacturing process, while also reducing the need for manual labor.

Challenges in AI development​

Artificial Intelligence market size is growing and it is said that it can grow up to $15.7 trillion by 2030, as quoted in the research paper https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/637967/EPRS_BRI(2019)637967_EN.pdf

As AI grows, the impact and challenges rise parallely as well. Let's see some of the most common challenges in Artificial Intelligence Development.

The pandemic has changed the way we live. People have become extremely conscious of every surface they touch and that worry takes up a significant part of the brain and leads to anxiety. There are some simple ways in which you can avoid this at spaces which require people to tap a RFID card or register their fingerprint to get access to the space. This can be done by using facial recognition along with the cameras placed at these entry points.