deep convolutional neural network (IEEE Access)
90
Structured Review
IEEE Access
deep convolutional neural network
Deep Convolutional Neural Network, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/deep+convolution/deep+convolutional+neural+networks/pm40398263-281-11-18
Average 90 stars, based on 1 article reviews
Deep Convolutional Neural Network, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/deep+convolution/deep+convolutional+neural+networks/pm40398263-281-11-18
Average 90 stars, based on 1 article reviews
deep convolutional neural network - by Bioz Stars,
2026-10
90/100 stars
Images
Related Articles
other:Article Title: A fractional-derivative kernel learning strategy for predicting residual life of rolling bearings Article Snippet: In the field of mechanical equipment maintenance, accurately estimating the remaining useful life (RUL) of rolling bearings is crucial for ensuring reliable equipment operation.. However, prevalent deep learning methods face challenges such as limited sample sizes, and ‘‘black-box’’ mechanisms.. To enhance the accuracy and interpretability of rolling bearing RUL prediction, a novel fractional-derivative kernel mean p-power error filtering algorithm (FrKMPE) is introduced. Article Title: Encoder-Embedded Feature Enhancement in Convolutional Neural Networks for Arabic Handwritten Recognition Article Snippet: [23] Ghanim, T. M., Khalil, Article Title: Pattern Separation Network Based on the Hippocampus Activity for Handwritten Recognition Article Snippet: [5] T. M. Ghanim, M. I. Khalil, and H. M. Abbas, ‘‘Comparative study on deep convolution neural networks DCNN-based offline Biomarker Discovery:Article Title: CUTTING-EDGE CNN APPROACHES FOR BREAST HISTOPATHOLOGICAL CLASSIFICATION: THE IMPACT OF SPATIAL ATTENTION MECHANISMS Article Snippet: This paper investigates advanced techniques for breast Histopathological Classification using two robust convolutional neural network (CNN) architectures: Inception V3 and VGG19.. Spatial attention mechanisms are integrated to enhance the models' capability to focus on crucial regions within histology images.. These enhancements improve diagnostic accuracy by allowing the models to concentrate on critical features for accurate detection. |