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  2. Latent diffusion model - Wikipedia

    en.wikipedia.org/wiki/Latent_Diffusion_Model

    The encoder part of the VAE takes an image as input and outputs a lower-dimensional latent representation of the image. This latent representation is then used as input to the U-Net. Once the model is trained, the encoder is used to encode images into latent representations, and the decoder is used to decode latent representations back into images.

  3. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    In text-to-image retrieval, users input descriptive text, and CLIP retrieves images with matching embeddings. In image-to-text retrieval, images are used to find related text content. CLIP’s ability to connect visual and textual data has found applications in multimedia search, content discovery, and recommendation systems. [31] [32]

  4. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.

  5. Convolutional neural network - Wikipedia

    en.wikipedia.org/wiki/Convolutional_neural_network

    A fully connected layer for an image of size 100 × 100 has 10,000 weights for each neuron in the second layer. Convolution reduces the number of free parameters, allowing the network to be deeper. [6] For example, using a 5 × 5 tiling region, each with the same shared weights, requires only 25 neurons.

  6. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A bottleneck block [1] consists of three sequential convolutional layers and a residual connection. The first layer in this block is a 1x1 convolution for dimension reduction (e.g., to 1/2 of the input dimension); the second layer performs a 3x3 convolution; the last layer is another 1x1 convolution for dimension restoration.

  7. Image derivative - Wikipedia

    en.wikipedia.org/wiki/Image_derivative

    Image derivatives can be computed by using small convolution filters of size 2 × 2 or 3 × 3, such as the Laplacian, Sobel, Roberts and Prewitt operators. [1] However, a larger mask will generally give a better approximation of the derivative and examples of such filters are Gaussian derivatives [ 2 ] and Gabor filters . [ 3 ]

  8. 50 Proud Pet Owners Share The Delightful Pets They Adopted In ...

    www.aol.com/90-incredibly-cute-rescue-animal...

    Meanwhile, for more tips and advice for the festive period, feel free to download PDSA's Christmas Survival Guide. #7 Found This Cold Little Guy In A Bush. I Think My Cat Has Adopted Him

  9. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    U-Net is a convolutional neural network that was developed for image segmentation. [1] The network is based on a fully convolutional neural network [2] whose architecture was modified and extended to work with fewer training images and to yield more precise segmentation.