4 useful recognition based Artificial Intelligence (AI) technologies

4 useful recognition-based Artificial Intelligence (AI) technologies  

Introduction

This article/blog is basically designed to discuss some useful recognition-based technologies of AI used by a machine to identify and recognize things/objects from the environment like a human being. AI is a branch of computer science that focuses on making the machine/computer more smart and able to take decisions like a gentleman. So, in this article/blog you will be able to know and learn about some essential and useful recognition-based technologies used in Artificial Intelligence (AI) with their application.

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI)

·       AI is a branch of computer science.

·       AI refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.

·       AI is used to create intelligent machines which can behave like a human, think like humans and be able to make decisions under different situations.

Some useful recognition based technologies used in Artificial Intelligence (AI) are as under:

Emotion recognition

·       Emotion recognition is the method/process of identifying human emotion based on the observation of visual and auditory non-verbal cues (facial, vocal, postural, heart rate, brain activity and gestural cues) displayed by a sender.

·       Emotion recognition is used to identify, detect and assess the emotional state of a human subject/patient.

·       Deep learning and Machine learning algorithms (Support Vector Machines (SVM), Naive Bayes and Maximum entropy) of AI are widely used in emotion recognition.

Image recognition in ML

·       Image recognition in ML refers to the ability of software to identify objects, places, people, writing and actions in images.

·       Image recognition can be achieved using machine vision technologies in combination with a camera and AI software.

·       Image recognition technology is widely used in Automobile Industry (in manufacturing self-driving cars), Gaming, Healthcare industry (in Microsurgical procedures using robots), Real-time emotion detection of patients, Merged reality, Retail industry, security industry, social media platforms, performing image content search, guiding autonomous robots, visual search engines and accident avoidance systems.

·       Image recognition technology is used by Google lens app used in smartphone’s camera to capture images and provide relevant information related to objects that it identifies.

·       Security devices that use Image recognition technology of AI are drones, security cameras and facial recognition biometric devices.

·       SimCam home security and home automation cameras are widely used for facial recognition and pet-monitoring.

·       Netatmo is a smart indoor camera that starts recording video only when the system detects any unknown/new faces.

Speech recognition

·       Speech recognition is also called automatic speech recognition (ASR), computer speech recognition or speech-to-text.

·       Speech recognition refers to a capability which enables a program to process human speech into written format.

·       Speech recognition is an interdisciplinary subfield of computer science and computational linguistics.

·       Speech recognition is used to identify words in spoken language.

·       Speech recognition is used in the mobile device and the smart speaker system used in the living room.

·       Some devices which use speech recognition technology are Alexa, Cortana, Google Assistant and Siri. These technologies are changing the way people interact with their devices, homes, cars and jobs.

Pattern recognition

·       Pattern recognition refers to the classification of data based on knowledge already gained or on statistical information extracted from patterns and /or their representation.

·       Pattern recognition in ML indicates the use of powerful algorithms for identifying the regularities in the given data.

·       Pattern recognition is widely used in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.

·       Pattern recognition is widely used in computer vision, speech recognition and face recognition.

·       Pattern recognition is also used to check whether a given email is spam or non-spam.