Xu et al., 2021 - Google Patents
Dct-based fast spectral convolution for deep convolutional neural networksXu et al., 2021
- Document ID
- 5022775163320180781
- Author
- Xu Y
- Nakayama H
- Publication year
- Publication venue
- 2021 International Joint Conference on Neural Networks (IJCNN)
External Links
Snippet
Spectral representations have been introduced into deep convolutional neural networks (CNNs) mainly for accelerating convolutions and mitigating information loss. However, repeated domain transformations and complex arithmetic of commonly-used Fourier …
- 230000003595 spectral 0 title abstract description 79
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/141—Discrete Fourier transforms
- G06F17/142—Fast Fourier transforms, e.g. using a Cooley-Tukey type algorithm
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/145—Square transforms, e.g. Hadamard, Walsh, Haar, Hough, Slant transforms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30312—Storage and indexing structures; Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US10796220B2 (en) | Systems and methods for vectorized FFT for multi-dimensional convolution operations | |
Zhou et al. | Review of research on lightweight convolutional neural networks | |
Xu et al. | Dct-based fast spectral convolution for deep convolutional neural networks | |
US10394929B2 (en) | Adaptive execution engine for convolution computing systems | |
CN108765247B (en) | Image processing method, device, storage medium and equipment | |
Kekre et al. | Inception of hybrid wavelet transform using two orthogonal transforms and it's use for image compression | |
Wang et al. | A novel image encryption scheme using chaos and Langton’s Ant cellular automaton | |
CN109858613B (en) | A compression method, system and terminal device for a deep neural network | |
Park | 2D discrete Fourier transform on sliding windows | |
CN106709441A (en) | Convolution theorem based face verification accelerating method | |
CN110020681A (en) | Point cloud feature extracting method based on spatial attention mechanism | |
Li et al. | A image encryption algorithm based on coexisting multi-attractors in a spherical chaotic system | |
Bahri et al. | Image feature extraction algorithm based on CUDA architecture: case study GFD and GCFD | |
CN110399826B (en) | End-to-end face detection and identification method | |
CN116883679B (en) | Ground object extraction method and device based on deep learning | |
CN115836330A (en) | Action identification method based on depth residual error network and related product | |
Moustafa et al. | Acceleration of super-resolution for multispectral images using self-example learning and sparse representation | |
Yang et al. | FDS_2D: rethinking magnitude-phase features for DeepFake detection | |
Prots’ko | Algorithm of Efficient Computation of DCT I–IV Using Cyclic Convolutions | |
CN118097252A (en) | Classification method and device for hyperspectral images | |
CN110321581A (en) | A kind of design method of the two-dimensional Fourier transform IP kernel based on HLS | |
Xu et al. | DCT based information-preserving pooling for deep neural networks | |
Ulicny et al. | Tensor reordering for cnn compression | |
Xu et al. | Shifted spatial-spectral convolution for deep neural networks | |
CN103345491A (en) | Method for quickly obtaining neighborhood by the utilization of Hash dividing barrels |