IEEE

An Interactive Residual Fusion Network for Lightweight Super-Resolution Reconstruction

Abstract: Benefitting from attention mechanisms and deepening convolutional layers, CNN-based single image super-resolution reconstruction (SISR) methods evolve rapidly. However, computational cost, ...
marktechpost

The Statistical Cost of Zero Padding in Convolutional Neural Networks (CNNs)

img = Image.open('/content/Gemini_Generated_Image_dtrwyedtrwyedtrw.png').convert('L') # Load as Grayscale img_array = np.array(img) / 255.0 # Normalize to [0, 1] plt ...
EurekAlert!

CornPheno: A game-changer in corn breeding with smartphone-based phenotyping

First, a Convolutional Neural Network (CNN) backbone is used to extract the image features. Then, a transformer encoder with progressive rectangle window attention is applied to these features to ...
Scientific Research Publishing

Dual-Dilated Large Kernel Convolution for Visual Attention Network ()

Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...
C&EN

Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...
Scientific Research Publishing

Li, Z., Yang, W., Peng, S., et al. (2020) A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
IEEE

Correlating Time Series With Interpretable Convolutional Kernels

Abstract: This study addresses the problem of convolutional kernel learning in univariate, multivariate, and multidimensional time series data, which is crucial for interpreting temporal patterns in ...