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CVonline Subject Linkages
Databases and indexing related concepts
Generic computer vision methods
Geometric and other image features and methods
Geometry and mathematics
Image physics related concepts
Image Processing Architectures & Control Structures
Image transformations and filters
Introductory visual neurophysiology
Introductory visual psychophysics/psychology
Motion and time sequence analysis related concepts
Non-sequential realization methods
Object, world and scene representations
Recognition and registration methods
Scene understanding/image analysis methods
Sensor fusion, registration and planning methods
Sensors and Properties
System models, calibration and parameter estimation methods
Visual learning related methods and concepts
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Non-sequential realization methods
A part of the
CVonline
computer vision resource summarizing the different non-sequential algorithmic structures commonly encountered in computer vision and image processing.
Convolutional, Deep, Recurrent Neural Networks
Convolutional neural network
(
CNN
, or
ConvNet
)
Deep neural networks
Long short-term memory
(
LSTM
)
R
ecurrent neural network
(
RNN
)
Transfer learning
Systolic arrays
Digital signal processing
/
Digital signal processor
Artificial neural networks
Hopfield networks
Kohonen networks
Perceptron networks
Radial basis function networks
Support vector machines
Parallel processing
approaches
GPU/GPGPU approaches
Multiple Instruction Multiple Data (MIMD)
/
Multiprocessing
Data parallelism
/
Domain decomposition methods
Single Instruction Multiple Data (SIMD)
Massively parallel systems
Vector processors
Programmable logic
approaches
Reconfigurable computing
VLSI
approaches
Dynamic Vision Sensor
Vision chips
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