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· 8 min read
Sushmith Banoth

A-step-by-step-guide-on-how-to-build-a-wildfire-identification-AI-model-using-no-code-computer-vision-tool-Navan-AI Wildfire prediction using computer vision is a field of study that involves leveraging computer vision techniques to analyze visual data for the detection and prediction of wildfires. Computer vision, a subfield of artificial intelligence, focuses on enabling computers to interpret and understand visual information from the world, such as images or videos.

· 6 min read
Sushmith Banoth

Vehicle type classification is the process of categorizing vehicles into different groups based on their design, functionality, and purpose. This classification is used in various industries, including transportation, automotive, and insurance, among others, to analyze data and make informed decisions. A-step-by-step-guide-on-how-to-build-a-vehicle-classification-AI-model-using-no-code-computer-vision-tool-Navan-AI

· 6 min read
Sushmith Banoth

Gesture classification using computer vision involves recognizing and categorizing hand or body movements captured by cameras as input, with the goal of inferring the intended gesture. This can be achieved through various techniques such as image processing, machine learning, and deep learning.

The process starts with capturing video or image data of the gestures, followed by preprocessing and feature extraction. After that, the features are fed into a machine-learning model that has been trained to recognize gestures, resulting in the classification of the input gesture. This technology has various applications in human-computer interaction, gaming, sign language recognition, and other fields.

A-step-by-step-guide-on-how-to-build-a-gesture-classification-AI-model-using-no-code-computer-vision-tool-Navan-AI

· 7 min read
Sushmith Banoth

Human 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. A-step-by-step-guide-on-how-to-build-an-emotion-recognition-AI-model-using-no-code-computer-vision-tool-Navan-AI

· 4 min read
Sushmith Banoth

In the previous blog, we discussed the applications of computer vision in the manufacturing industry.

quality-control

This blog explains how to use navan.ai, a no-code computer vision platform to build an image classification model to classify damaged and intact medical packages.

· 5 min read
Sushmith Banoth

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.

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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.