然而,相反地,融合太多的层可能带来冗余信息,会大大降低性能。 六、总结 本文提出了一种新的DL-based 分类方法DFFN。与之前的网络相比,DFFN主要采用残差连接来增加模型的深度,可以提取更深层的特征。同时使用特征融合机制充分利用多层特征。
(2018) implement the deep feature fusion network (DFFN), composed by stages or branches of CONV layers connected with internal residual units, whose features are concatenated at the end (before the final classification). Li et al. (2019b) develop the multiscale deep middle-level feature ...
The first step is image defects detection based on convolutional auto-encoder (U-Net) and deep feature fusion network (DFFN-Net). The second step is a depth map reconstruction with the exemplar-based and the anisotropic gradient concepts. The proposed modified block fusion algorithm uses a ...
SWNet optimizes feature extraction through multiple pathways, emphasizing network width augmentation to enhance efficiency. The proposed model addresses potential biases associated with skin conditions, particularly in individuals with darker skin tones or excessive hair, by incorporating feature fusion to ...
MFFN: image super-resolution via multi-level features fusion network. Vis Comput. 2023. https://doi.org/10.1007/s00371-023-02795-0. 28. Chen Y, Xia R, Yang K, Zou K. DGCA: high resolution image inpainting via DR-GAN and contextual attention. Mul- timed ...
[26] introduced Non-Intrusive Load Monitoring using a Deep Convolutional Generative Adversarial Network for Prediction (NILM-GAN). Propose a technique for modifying the feature space utilizing the EMBED dataset's visual representation and the deep convolutional GAN (DCGAN)—finally, the test ...
& DVFNet A deep feature fusion-based model for the multiclassification of skin cancer utilizing dermoscopy images. PLoS One. 19, e0297667 (2024). 52. Chanda, D. et al. A new deep convolutional ensemble network for skin cancer classification. Biomed. Signal. Process. Control. 89, 105757 (...
许多其他深度学习模型更适合处理时间序列数据,例如循环神经网络(Recurrent Neural Networks, RNNs)和卷积神经网络(Convolutional Neural Network, CNNs),这些模型专门设计用于捕捉时间序列数据中的时间依赖性和局部模式。 (2) 基于卷积神经网络模型:CNN最初由Fukushima[21]于1982年提出,其灵感来自于动物视觉皮层的结构和...
种深度学习方法的比较,包括包括SVM、EMP、联合备用表示(JSR)和边缘保持滤波(EPF),3D-CNN(《Deep feature extraction and classification of hyperspectral images based on convolutional neural networks》), Gabor-CNN,带有像素对特征的CNN (CNN-PPF),暹罗CNN (S-CNN) , 3D-GAN和深度特征融合网络(DFFN),用于HSI...
An enhanced 3D Convolutional Neural Network, which contains a spatiotemporal attention layer, is utilized in a Siamese architecture. Various analyses are carried out on the control parameters, feature importance, and reproducibility of results. Our technique is tested on four datasets: Celeb-DF, ...