在压缩域中减少复杂性的卷积神经网络
Hamdan Abdellatef1, Lina J Karam2
1School of Engineering - Electrical & Computer Engineering Department, Lebanese American University, Byblos, Lebanon.
概括
本研究介绍了对卷积神经网络 (CNN) 的压缩域学习,显著加快图像处理. 通过处理JPEG压缩图像,CNN可以实现更快的速度,具有可比的准确性和更少的数据存储.
科学领域:
- 计算机视觉 计算机视觉
- 深度学习 (Deep Learning) 是一种深度学习.
- 图像处理 图像处理
背景情况:
- 深度神经网络,特别是卷积神经网络 (CNN),在计算机视觉方面表现出色,但计算密集.
- 图像通常以JPEG等压缩格式存储和传输,这对传统的空间域CNN构成了挑战.
- 现有的CNN很慢,需要大量的计算资源,这限制了它们的实际应用.
研究的目的:
- 通过在压缩域中执行学习和推断来降低计算复杂性并提高流行的CNN的速度.
- 在神经网络中开发有效处理JPEG压缩图像的方法.
- 保持分类准确性,同时提高深度学习模型的效率.
主要方法:
- 提出了一种基于图形的新型频道选择方法,以识别和保留重要的频率组件.
- 直接在JPEG压缩图像数据上实现学习和推断.
- 通过抛弃无关紧要的频率组件和消除不必要的网络层来降低计算复杂性.
- 引入了带有部分编码的预处理步骤,以提高对压缩引起的扭曲的弹性.
主要成果:
- 与空间域ResNet-50相比,在压缩域中运行的修改后的ResNet-50实现了高达70%的更快性能.
- 在压缩域和空间域CNN之间保持了类似的分类准确性.
- 使用高度压缩数据的培训导致了良好的分类准确性,培训数据存储需求减少了多达93%.
结论:
- 在压缩域中执行CNN学习和推断是一个可行的策略,可以显著提高速度并减少计算负载.
- 提出的频道选择和部分编码方法有效地解决了与压缩图像处理相关的挑战.
- 压缩域CNN为高效准确的计算机视觉任务提供了有希望的方法,特别是在资源有限的环境中.
相关概念视频
01:24Convolution: Math, Graphics, and Discrete Signals
268
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
268
01:20Convolution Properties I
155
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
155
01:17Convolution Properties II
210
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
210
01:20Downsampling
164
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
164
01:22Block Diagram Reduction
220
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
220
01:22Upsampling
240
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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