◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Guannan Lv

3 papers hereh-index 6166 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3
same name
  • Guannan Lv — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedImage Blind Denoising Using Dual Convolutional Neural Network with Skip Connection

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2024

Two-stage Progressive Residual Dense Attention Network for Image Denoising

Wencong Wu, An Ge, Guannan Lv +3

Deep convolutional neural networks (CNNs) for image denoising can effectively exploit rich hierarchical features and have achieved great success. However, many deep CNN-based denoi…

cs.CV2023★ 1 cited

Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection

Wencong Wu, Shicheng Liao, Guannan Lv +2

In recent years, deep convolutional neural networks have shown fascinating performance in the field of image denoising. However, deeper network architectures are often accompanied…

cs.CV2023

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

Wencong Wu, Guannan Lv, Yingying Duan +3

Noise removal of images is an essential preprocessing procedure for many computer vision tasks. Currently, many denoising models based on deep neural networks can perform well in r…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.