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一个新的剩余块:用Conv3×3取代Conv1×1,并堆叠更多的卷积
XiuJian Hu1, Guanglei Sheng1,2, Daohua Zhang1
1Department of Electronic and Information Engineering, Bozhou University, Bozhou, Anhui, China.
PeerJ. Computer science
|June 22, 2023
概括
一种新的残余结构提高了计算机视觉中的神经网络性能. 这种改进的设计可以在基准数据集上实现更高的准确性,而不是像ResNet50.50.这样的现有模型.
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.
- 人工智能的人工智能
背景情况:
- 其余结构对于计算机视觉中的神经网络性能至关重要.
- 传统的残余网络在接收场大小,通道和空间信息处理方面存在局限性.
研究的目的:
- 提出一种新的残留结构,克服经典残留网络的局限性.
- 为了增强有效的受体场,通道信息融合和空间特征提取.
主要方法:
- 在剩余结构中修改身份映射和下方采样块.
- 除研究,以验证道信息融合和空间特征提取的性能.
- 使用Cifar10和Cifar100数据集上的新型结构设计和测试一个非深层卷积神经网络 (CNN).
主要成果:
- 新的残余结构在道信息融合和空间特征提取方面表现出卓越的性能.
- 拟议的网络模型在基准数据集上实现了比主流网络 (ResNet50,ResNeXt50,SeResNet152) 更高的准确性.
- 实现了比ResNet50高3.08%的精度,比ResNeXt50高1.38%的精度.
- 在50个更少的培训时代中,SeResNet152的表现优于0.29%.
结论:
- 拟议的新型残余结构显著提高了计算机视觉任务的神经网络性能.
- 增强的有效接收场和特征提取能力为现有架构提供了有竞争力的替代方案.
- 该模型对高效和高准确度的图像识别应用非常有希望.
相关概念视频
01:24Convolution: Math, Graphics, and Discrete Signals
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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...
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01:17Convolution Properties II
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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...
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01:20Convolution Properties I
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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:
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01:20Deconvolution
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Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
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01:07Residual Plots
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A residual plot is a statistical representation of data used to analyze correlation and regression results. It helps verify the requirements for drawing specific conclusions about correlation and regression. To obtain the residual plot, first, the residual for each data value is calculated, which is simply the vertical distance between the observed and the predicted value obtained from the regression equation.
When the residual values are plotted against the variable x, it is called a residual...
When the residual values are plotted against the variable x, it is called a residual...
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01:11Residuals and Least-Squares Property
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The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
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