IEEE

Hyperspectral Image Classification Using Groupwise Separable Convolutional Vision Transformer Network

Abstract: Recently, vision transformer (ViT)-based deep learning (DL) models have achieved remarkable performance gains in hyperspectral image classification (HSIC) due to their abilities to model ...

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Investing.com Australia

WiMi Hologram stock soars after launching quantum neural network tech

Investing.com -- WiMi Hologram Cloud Inc. (NASDAQ:WIMI) stock surged 11.3% on Monday after the company announced the launch of its independently developed Quantum Convolutional Neural Network for ...
EurekAlert!

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

Corn is one of the world's most important crops, critical for food, feed, and industrial applications. In 2023, corn production in China alone accounted for 41% of total crop production, highlighting ...
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 ...
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 ...
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 ...