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  2. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A basic block is the simplest building block studied in the original ResNet. [1] This block consists of two sequential 3x3 convolutional layers and a residual connection. The input and output dimensions of both layers are equal. Block diagram of ResNet (2015). It shows a ResNet block with and without the 1x1 convolution.

  3. Kaiming He - Wikipedia

    en.wikipedia.org/wiki/Kaiming_He

    Upload file; Search. Search. ... Download QR code; Print/export ... Institute of Technology and is known as one of the creators of residual neural network (ResNet ...

  4. Inception (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Inception_(deep_learning...

    As an example, a single 5×5 convolution can be factored into 3×3 stacked on top of another 3×3. Both has a receptive field of size 5×5. The 5×5 convolution kernel has 25 parameters, compared to just 18 in the factorized version. Thus, the 5×5 convolution is strictly more powerful than the factorized version.

  5. File:ResNet block.svg - Wikipedia

    en.wikipedia.org/wiki/File:ResNet_block.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  6. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    Residual connections, or skip connections, refers to the architectural motif of +, where is an arbitrary neural network module. This gives the gradient of ∇ f + I {\displaystyle \nabla f+I} , where the identity matrix do not suffer from the vanishing or exploding gradient.

  7. Studentized residual - Wikipedia

    en.wikipedia.org/wiki/Studentized_residual

    The usual estimate of σ 2 is the internally studentized residual ^ = = ^. where m is the number of parameters in the model (2 in our example).. But if the i th case is suspected of being improbably large, then it would also not be normally distributed.

  8. Motion compensation - Wikipedia

    en.wikipedia.org/wiki/Motion_compensation

    Variable block-size motion compensation (VBSMC) is the use of BMC with the ability for the encoder to dynamically select the size of the blocks. When coding video, the use of larger blocks can reduce the number of bits needed to represent the motion vectors, while the use of smaller blocks can result in a smaller amount of prediction residual ...

  9. Readers–writer lock - Wikipedia

    en.wikipedia.org/wiki/Readers–writer_lock

    In computer science, a readers–writer (single-writer lock, [1] a multi-reader lock, [2] a push lock, [3] or an MRSW lock) is a synchronization primitive that solves one of the readers–writers problems. An RW lock allows concurrent access for read-only operations, whereas write operations require exclusive access.