What do you mean by Project in DeepDream?

Model Merging is the process of combining many machine-learning models to achieve a variety of goals, including strengthening generalization, boosting accuracy, boosting robustness, and optimizing resource use.

Neural networks, specifically Convolutional Neural Networks (CNNs), are used in DeepDream and other ‘deep art’ techniques to produce images. The process involves feeding an image through the network, calculating gradients to identify areas of high activation, and then modifying the image to further amplify the patterns and features the network recognizes within it.

The preferred model for generating realistic and high-definition imagery is Photonic. Its mechanism is aimed at producing images as near to reality as possible, with a high degree of clarity.

DeepDream controls the degree of alteration of an image throughout the algorithm. The process leads to:

• Production of strong patterns and dramatic picture modification
• Applies smoother gradual transformation.

Gradients are calculated in DeepDream by following the steps given below:

• Choose a specific layer in the network to focus on
• After the image has been processed by the neural network, the degree to which the selected layer activates
• Compute the gradient to see how much each pixel in the image influences the layer's activation
• Modify the image's pixels according to the gradient to emphasize patterns that the network deems intriguing
• Repeat this several times to intensify those patterns and produce the surreal feeling.