Beyond Convolution: A Taxonomy of Structured Operators for Learning-Based Image Processing

Export BriefConnect with Author
View PDF ↗
PDF Viewer
Open Full PDF

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (36)

[1]
Optimal Weighted Convolution for Classification and Denosing
2025Simone Cammarasana, Giuseppe Patané
[2]
Analysis and comparison of high-performance computing solvers for minimisation problems in signal processing
2024Simone Cammarasana, Giuseppe Patané
[3]
Adaptive Membership Functions and F-Transform
2024Simone Cammarasana, Giuseppe Patané
[4]
Omni-Dimensional Dynamic Convolution
2022Chao Li, Aojun Zhou et al.
[5]
Learning-based low-rank denoising
2022Simone Cammarasana, G. Patané
[6]
Simple Baselines for Image Restoration
2022Liangyu Chen, Xiaojie Chu et al.
[7]
Kernel-Based Sampling of Arbitrary Signals
2021Simone Cammarasana, G. Patané
[8]
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
2020Alexey Dosovitskiy, Lucas Beyer et al.
[9]
Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
2020Angelos Katharopoulos, Apoorv Vyas et al.
[10]
Dynamic Convolution: Attention Over Convolution Kernels
2019Yinpeng Chen, Xiyang Dai et al.
[11]
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
2019Qilong Wang, Banggu Wu et al.
[12]
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View
2019Deli Chen, Yankai Lin et al.
[13]
Multi-Level Wavelet Convolutional Neural Networks
2019Pengju Liu, Hongzhi Zhang et al.
[14]
CBAM: Convolutional Block Attention Module
2018Sanghyun Woo, Jongchan Park et al.
[15]
An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
2018Rosanne Liu, J. Lehman et al.
[16]
Non-local Neural Networks
2017X. Wang, Ross B. Girshick et al.
[17]
Attention is All you Need
2017Ashish Vaswani, Noam Shazeer et al.
[18]
Deformable Convolutional Networks
2017Jifeng Dai, Haozhi Qi et al.
[19]
Neural Architecture Search with Reinforcement Learning
2016Barret Zoph, Quoc V. Le
[20]
An overview of gradient descent optimization algorithms
2016Sebastian Ruder

Showing 20 of 36 references

Founder's Pitch

"This paper proposes a taxonomy of structured operators to enhance learning-based image processing beyond traditional convolution."

Image ProcessingScore: 2View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

0/4 signals

0

Quick Build

0/4 signals

0

Series A Potential

0/4 signals

0

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 3/12/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.

Related Papers

Loading…

Related Resources