Dual Convolutional

Dual convolutional neural networks (DCNNs) employ two convolutional neural networks in parallel or sequentially to enhance performance in various tasks. Current research focuses on applications ranging from image denoising and blind source separation (like non-intrusive load monitoring) to more complex problems such as melanoma diagnostics and bundle recommendations, often incorporating attention mechanisms or hypergraph structures to improve information processing. The effectiveness of DCNNs stems from their ability to extract complementary features or handle multiple aspects of a problem simultaneously, leading to improved accuracy and efficiency in diverse fields like computer vision and signal processing.

Papers

September 18, 2024

Dual-Layer Training and Decoding of Large Language Model with Simultaneously Thinking and Speaking
Ningyuan Xi, Xiaoyu Wang, Yetao Wu, Teng Chen, Qingqing Gu, Jinxian Qu, Zhonglin Jiang, Yong Chen, Luo Ji
Large Language Model Language Model Accurate Decoding Human Thinking Dual Convolutional

December 18, 2023

Hypergrah-Enhanced Dual Convolutional Network for Bundle Recommendation
Kangbo Liu, Yang Li, Yaoxin Wu, Zhaoxuan Wang, Xiaoxu Wang
Hypergraph Convolutional Network Bundle Sale Data Bundle Recommendation Dual Convolutional

December 14, 2023

A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics
Marie Bø-Sande, Edvin Benjaminsen, Neel Kanwal, Saul Fuster, Helga Hardardottir, Ingrid Lundal, Emiel A. M. Janssen, Kjersti Engan
Convolutional Neural Network Prognostic Prediction Diagnostic Model Melanoma Skin Cancer Melanoma Diagnosis Dual Convolutional Prognosis Model

April 4, 2023

February 11, 2023

MSDC: Exploiting Multi-State Power Consumption in Non-intrusive Load Monitoring based on A Dual-CNN Model
Jialing He, Jiamou Liu, Zijian Zhang, Yang Chen, Yiwei Liu, Bakh Khoussainov, Liehuang Zhu
Power Consumption Non Intrusive Load Monitoring Dual Convolutional

February 15, 2022

DualConv: Dual Convolutional Kernels for Lightweight Deep Neural Networks
Jiachen Zhong, Junying Chen, Ajmal Mian
Neural Network CNN Architecture Convolutional Kernel Lightweight Deep Dual Convolutional

November 16, 2021

Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks
Xiao Pan, T. Y. Yang
Damage Detection Computer Vision Technique YOLO Series Damage Assessment Advanced Object Detection Dual Convolutional Concrete Structure

Dual Convolutional

Papers

Dual-Layer Training and Decoding of Large Language Model with Simultaneously Thinking and Speaking

Hypergrah-Enhanced Dual Convolutional Network for Bundle Recommendation

A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics

Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection

DCANet: Dual Convolutional Neural Network with Attention for Image Blind Denoising

MSDC: Exploiting Multi-State Power Consumption in Non-intrusive Load Monitoring based on A Dual-CNN Model

DualConv: Dual Convolutional Kernels for Lightweight Deep Neural Networks

Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks