The Malaysian Reserve

WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ...
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 ...
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 ...
Scientific Research Publishing

A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification ()

1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...
Frontiers

Numerical investigation of the effective receptive field and its relationship with convolutional kernels and layers in convolutional neural network

1 Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention, Shantou University, Shantou, China 2 First Institute of Oceanography and Key Laboratory of Marine Science and ...
marktechpost

Exploring Robustness: Large Kernel ConvNets in Comparison to Convolutional Neural Network CNNs and Vision Transformers ViTs

Robustness is crucial for deploying deep learning models in real-world applications. Vision Transformers (ViTs) have shown strong robustness and state-of-the-art performance in various vision tasks ...
IEEE

GMConv: Modulating Effective Receptive Fields for Convolutional Kernels

Abstract: In convolutional neural networks (CNNs), the convolutions are conventionally performed using a square kernel with a fixed $N \times N$ receptive field (RF ...