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5 days ago · The input stem used cascaded 3 × 3 convolution layers with 32, 32, and 64 output channels, respectively, and a max pooling layer in the residual block to down-sample the feature map. The output feature map was subsequently sent through four feature extraction stages to capture all high-dimensional semantic features.
2 days ago · Convolution has applications that include probability, statistics, acoustics, spectroscopy, signal processing and image processing, geophysics, engineering, physics, computer vision and differential equations. The convolution can be defined for functions on Euclidean space and other groups (as algebraic structures).
4 days ago · Convolution. Definition: If functions f and g are piecewise continuous on [0, ∞), then the integral. (f ∗ g)(t) = g ∗ f(t) = ∫t 0f(τ)g(t − τ)dτ = ∫t 0g(τ)f(t − τ)dτ. is called the convolution of f and g and is denoted by f ∗ g(t). Evaluation of a convolution belongs to the class of ill-posed problems.
2 days ago · An x-ray tube functions as a specific energy converter, receiving electrical energy and converting it into two other forms of energy: x-radiation (1%) and heat (99%). Heat is considered the undesirable product of this conversion process; therefore x-radiation is created by taking the energy from the electrons and converting it into photons.
1 day ago · Convolution is widely used in various computer vision tasks. In most existing literature, convolution and self-attention are often combined, with the focus primarily on using convolution as a branch to extract local features. For instance, MPViT added convolutional branches to provide local features for multi-scale encoders. It combined ...
3 days ago · An award-winning, radiologic teaching site for medical students and those starting out in radiology focusing on chest, GI, cardiac and musculoskeletal diseases containing hundreds of lectures, quizzes, hand-out notes, interactive material, most commons lists and pictorial differential diagnoses
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2 days ago · Morphological transformations are some simple operations based on the image shape. It is normally performed on binary images. It needs two inputs, one is our original image, second one is called structuring element or kernel which decides the nature of operation. Two basic morphological operators are Erosion and Dilation.
