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1. YOLO v4 is a complex architecture for object detection. 2. SIFT is invariant to scale and angle due to its keypoint detection and descriptor extraction techniques. 3. GANs and VAEs differ in their approach to generative modeling.
YOLO v4 is a state-of-the-art object detection architecture that uses a deep neural network with multiple layers.
SIFT (Scale-Invariant Feature Transform) is invariant to scale and angle beca...
The loss function for GAN is based on the minimax game between the generator and discriminator networks.
The generator tries to minimize the loss by generating realistic samples.
The discriminator tries to maximize the loss by correctly classifying real and generated samples.
The loss function typically involves cross-entropy or binary cross-entropy.
The generator and discriminator update their weights based on the gradien...
The loss function for VAE is a combination of a reconstruction loss and a regularization loss.
The reconstruction loss measures the difference between the input and the output of the VAE.
The regularization loss encourages the latent space to follow a prior distribution, typically a Gaussian distribution.
The total loss is the sum of the reconstruction loss and the regularization loss.
Commonly used reconstruction loss fun...
TCS
Accenture
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