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augmentation
To train a model or use transfer learning in machine vision, there must be enough data. Data Augmentation is...
Train, Test, and Validation Datasets
An artificial intelligence model output is affected by how we divide the input dataset. There are several factors to...
Data-Driven approach
An AI model’s performance can be increased by either improving the dataset or the model’s structure. The purpose of...
Tensorboard
In this article, we will introduce Tensorboard and explain how it can be used on AIEX....
Loss-Function
The majority of machine learning algorithms work by minimizing or maximizing an 'objective function'. Loss Functions are a group...
backbone
Backbone is a network that extracts a feature map of the input image , the map is then utilized...
evaluation metrics
This article examines the different metrics used to evaluate machine vision models, and the metrics implemented on the AIEX...
object detection
Object detection is focused on identifying objects of interest in digital photographs using a computer vision model. In this...