MindMap Gallery convolutional neural network
The detailed architecture of the convolutional neural network, the bottleneck of the fully connected network, is that as the data size of the image becomes larger, the hidden layer network will be very complicated, come and take a look!
Edited at 2023-07-27 22:50:42This organizational chart, created using EdrawMax, illustrates the hierarchical structure of the Tesla Supercharger Network team. It showcases the chain of command starting from the Chief Executive Officer (CEO) down to various department heads and their respective team members. Each individual's role is clearly defined, showing how different functions such as planning, project construction, power & energy, and operations & service are organized to efficiently manage and expand the Supercharger network globally.
This 2026 Event Countdown Calendar, specifically highlighting the Christmas countdown and created via EdrawMax, presents a detailed monthly breakdown. Each month features a grid layout with a countdown mechanism towards significant events, especially Christmas. The use of red for countdown numbers creates a striking contrast, making it easy to track the days remaining until the big event. It's a perfect tool for those eagerly anticipating Christmas and wanting to plan related activities in advance.
This 2026 Holiday Planning Calendar, crafted with EdrawMax, offers a well-organized monthly view. Each month displays a grid of dates, with major holidays clearly marked. The color-coded design, using red and blue accents, helps distinguish different months and holidays at a glance. It serves as an excellent resource for planning vacations, family gatherings, or any events around holiday periods, ensuring you can make the most of your time off throughout the year.
This organizational chart, created using EdrawMax, illustrates the hierarchical structure of the Tesla Supercharger Network team. It showcases the chain of command starting from the Chief Executive Officer (CEO) down to various department heads and their respective team members. Each individual's role is clearly defined, showing how different functions such as planning, project construction, power & energy, and operations & service are organized to efficiently manage and expand the Supercharger network globally.
This 2026 Event Countdown Calendar, specifically highlighting the Christmas countdown and created via EdrawMax, presents a detailed monthly breakdown. Each month features a grid layout with a countdown mechanism towards significant events, especially Christmas. The use of red for countdown numbers creates a striking contrast, making it easy to track the days remaining until the big event. It's a perfect tool for those eagerly anticipating Christmas and wanting to plan related activities in advance.
This 2026 Holiday Planning Calendar, crafted with EdrawMax, offers a well-organized monthly view. Each month displays a grid of dates, with major holidays clearly marked. The color-coded design, using red and blue accents, helps distinguish different months and holidays at a glance. It serves as an excellent resource for planning vacations, family gatherings, or any events around holiday periods, ensuring you can make the most of your time off throughout the year.
convolutional neural network
Fully Connected Network Bottleneck
As the data size of the image increases, the hidden layer network will become very complex.
convolutional neural network
layer structure
convolution layer
Convolution kernel
Now for the convolution kernel group
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The depth of the feature response map group is equal to the number of convolution kernels
Different feature response maps reflect the response effect of the input image to different convolution kernels.
The values at different positions on the same feature response map represent the response results of different positions on the input image to the same convolution kernel.
Convolution step size
Perform convolution operations at specified intervals
border padding
effect
Keep input and output sizes consistent
The most common is zero padding
activation layer
Pooling layer
Perform each feature response map independently, reduce the width kernel height of each map in the map group, reduce the number of parameters of subsequent convolutional layers, increase the receptive field, and thereby control overfitting.
operate
Pooling a certain area of the feature response map means specifying a value in the area to represent the entire area.
Common types
max pooling
Equivalent to non-maximizing suppression
average pooling
hyperparameters
pooling window
Pooling step size
Fully connected layer
loss function
cross entropy loss
optimization
SGD
SGD with momentum
ADAM
image enhancement
question
Overfitting occurs because there are too few learning samples, resulting in the inability to train a model that can generalize to new data.
Generate more training data from existing training samples by augmenting the samples with a variety of random transformations that produce credible images
Purpose
Allow the model to observe more content of the data, thereby having better generalization capabilities
sample enhancement
Random scaling and cutout
Training stage: Randomly deduct at different scales and different areas
Testing phase: Withdraw according to a predefined method
color dither
Translation, rotation, distortion, cropping, etc.