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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 .
The algorithm works as follows: consider a binary search tree for the items in question. Each node of the tree has a one-bit flag denoting "go left to insert a pseudo-LRU element" or "go right to insert a pseudo-LRU element". To find a pseudo-LRU element, traverse the tree according to the values of the flags.
Source image of size 8x8. Network built from the bitmap. The source is on the left, the sink on the right. The darker an edge is, the bigger is its capacity. a i is high when the pixel is green, b i when the pixel is not green. The penalty p ij are all equal. [31] In their book, Kleinberg and Tardos present an algorithm for segmenting an image ...
This phenomenon is commonly experienced when using the first-in first-out page replacement algorithm. In FIFO, the page fault may or may not increase as the page frames increase, but in optimal and stack-based algorithms like LRU, as the page frames increase, the page fault decreases. László Bélády demonstrated this in 1969. [1]
Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. [ 1 ] It is used in computer vision , medical imaging , [ 2 ] military automatic target recognition , and compiling and analyzing images and data from ...
The random walker algorithm is an algorithm for image segmentation. In the first description of the algorithm, [1] a user interactively labels a small number of pixels with known labels (called seeds), e.g., "object" and "background". The unlabeled pixels are each imagined to release a random walker, and the probability is computed that each ...
The theoretically optimal page replacement algorithm (also known as OPT, clairvoyant replacement algorithm, or Bélády's optimal page replacement policy) [3] [4] [2] is an algorithm that works as follows: when a page needs to be swapped in, the operating system swaps out the page whose next use will occur farthest in the future. For example, a ...
In 2017, Saglam and Baykan used Prim's sequential representation of minimum spanning tree and proposed a new cutting criterion for image segmentation. [7] They construct the MST with Prim's MST algorithm using the Fibonacci Heap data structure. The method achieves an important success on the test images in fast execution time.