#3d image process

Supervised Learning: KNN is a supervised learning algorithm, meaning it learns from labeled data to make predictions. Instance-Based Learning: KNN is also considered an instance-based or lazy learning algorithm because it stores the entire training dataset and performs computations only when making predictions. 

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Supervised Learning: KNN is a supervised learning algorithm, meaning it learns from labeled data to make predictions. 

Instance-Based Learning: KNN is also considered an instance-based or lazy learning algorithm because it stores the entire training dataset and performs computations only when making predictions. 

Distance Metric: KNN relies on a distance metric to measure the similarity or distance between data points. 

Finding Nearest Neighbors:

For a new, unlabeled data point, KNN identifies the "k" nearest neighbors in the training data based on the chosen distance metric.

Classification: In classification tasks, the new data point is assigned to the class that is most common among its "k" nearest neighbors.

Regression: In regression tasks, the predicted value for the new data point is the average of the values of its "k" nearest neighbors. 

DARK PHANTOM ALGORITHM ⬇⬇⬇⬇⬇

Supervised Learning: KNN is a supervised learning algorithm, meaning it learns from labeled data to make predictions. 

Instance-Based Learning: KNN is also considered an instance-based or lazy learning algorithm because it stores the entire training dataset and performs computations only when making predictions. 

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Photography and Artistic Effects: In photography, image fusion can be used for artistic purposes, such as blending two images together to create surreal or blended effects. For example, blending a portrait with a landscape or combining different lighting conditions.

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