Pattern Recognition is the science of making inferences from the perceptual data using the tools from statistics, probability, computational geometry, machine learning, signal processing and algorithm design.
The applications of pattern recognition are:
- Machine Vision:
A machine vision system captures images via a camera and analyzes them to produce descriptions of images=d objects. For example, during inspection in manufacturing industry when the manufactured objects are passed through the camera, the images have to be analyzed online.
- Computer Aided Diagnosis (CAD):
CAD helps to assist doctors in making diagnostic decision. Computer assisted diagnosis has been applied in medical field such as X-rays, ECGs, ultrasound images etc.
- Speech Recognition:
This process recognizes the spoken information. In this the software in built around a pattern recognition system which recognizes the spoken text ans translated it into ASCII characters which are shown on the screen. In this we can also identify the identity of speaker.
- Character Recognition:
This application recognizes both letter and number. In this the optically scanned image is provided as input and alphanumeric characters are generated as output. Its major implication is in automation and information handling. It is also used in page readers, zip code, license plate etc.
In this the 3-D images such as structured light, laser, stereo etc is provided as input and as a result we can identify the objects.
- Fingerprint Identification:
In this the input image is obtained from fingerprint sensors and by this technique various fingerprint classes are obtained and we can identify the owner of the fingerprint.
- Industrial Automation:
In this we provide the intensity or range image of the product and by this the defective or non-defective product is identified.
- Machine Learning - Applications
- Phyllotaxis pattern in Python | A unit of Algorithmic Botany
- Pattern Recognition | Introduction
- Python | Named Entity Recognition (NER) using spaCy
- ML | Implement Face recognition using k-NN with scikit-learn
- Python | Speech recognition on large audio files
- ML | Frequent Pattern Growth Algorithm
- Pattern Recognition | Basics and Design Principles
- Top Machine Learning Applications in 2019
- Python | Multiple Face Recognition using dlib
- Python | Face recognition using GUI
- Object Detection vs Object Recognition vs Image Segmentation
- Deep Face Recognition
- ML | Face Recognition Using PCA Implementation
- ML | Face Recognition Using Eigenfaces (PCA Algorithm)
- FaceNet - Using Facial Recognition System
- Human Activity Recognition - Using Deep Learning Model
- License Plate Recognition with OpenCV and Tesseract OCR
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