Paper Citation Record · LEDGER

Optimal Weighted Convolution for Classification and Denosing

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.24558.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.24558 v1

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Outbound references

Observation 0c862815-76d6-43fd-94b8-4a4cf479bdf1 · outbound

This paper cites A new convolution neural layer based on weights constraints.

Optimal Weighted Convolution for Classification and Denosing A new convolution neural layer based on weights constraints

Reference 1

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This paper cites Ntire 2017 challenge on single image super-resolution: Dataset and study.

Optimal Weighted Convolution for Classification and Denosing Ntire 2017 challenge on single image super-resolution: Dataset and study

Reference 2

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This paper cites Noise2Self: Blind Denoising by Self-Supervision.

Optimal Weighted Convolution for Classification and Denosing Noise2Self: Blind Denoising by Self-Supervision

Reference 3

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Optimal Weighted Convolution for Classification and Denosing Simple baselines for image restoration

Reference 4

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Optimal Weighted Convolution for Classification and Denosing Dynamic convolution: Attention over convolution kernels

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Optimal Weighted Convolution for Classification and Denosing Convolutional kernel networks for graph-structured data

Reference 6

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This paper cites Real-time denoising of ultrasound images based on deep learning.

Optimal Weighted Convolution for Classification and Denosing Real-time denoising of ultrasound images based on deep learning

Reference 7

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Optimal Weighted Convolution for Classification and Denosing Analysis and comparison of high-performance computing solvers for minimisation problems in signal processing

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Optimal Weighted Convolution for Classification and Denosing Weighted convolutional neural network ensemble

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Optimal Weighted Convolution for Classification and Denosing Deep learning for computational chemistry

Reference 10

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This paper cites CascadedGaze: Efficiency in Global Context Extraction for Image Restoration.

Optimal Weighted Convolution for Classification and Denosing CascadedGaze: Efficiency in Global Context Extraction for Image Restoration

Reference 11

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This paper cites Generalizing the convolution operator in convolutional neural networks.

Optimal Weighted Convolution for Classification and Denosing Generalizing the convolution operator in convolutional neural networks

Reference 12

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Optimal Weighted Convolution for Classification and Denosing Weighted channel dropout for regularization of deep convolutional neural network

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Optimal Weighted Convolution for Classification and Denosing Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 14

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Optimal Weighted Convolution for Classification and Denosing Deep residual learning for image recognition

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Optimal Weighted Convolution for Classification and Denosing Backpropagation and stochastic gradient descent method

Reference 16

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This paper cites Variable weight algorithm for convolutional neural networks and its applications to classification of seizure phases and types.

Optimal Weighted Convolution for Classification and Denosing Variable weight algorithm for convolutional neural networks and its applications to classification of seizure phases and types

Reference 17

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Optimal Weighted Convolution for Classification and Denosing Hyper-parameter optimization of deep learning model for prediction of parkinson’s disease

Reference 18

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Optimal Weighted Convolution for Classification and Denosing Air learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation

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Optimal Weighted Convolution for Classification and Denosing Noise2void-learning denoising from single noisy images

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Optimal Weighted Convolution for Classification and Denosing Learning multiple layers of features from tiny images

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Optimal Weighted Convolution for Classification and Denosing Adam: A Method for Stochastic Optimization

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Optimal Weighted Convolution for Classification and Denosing Network In Network

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Optimal Weighted Convolution for Classification and Denosing Pay attention to mlp s

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Optimal Weighted Convolution for Classification and Denosing Noise2Noise: Learning Image Restoration without Clean Data

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Optimal Weighted Convolution for Classification and Denosing Omni-dimensional dynamic convolution

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Optimal Weighted Convolution for Classification and Denosing Convolutional kernel networks

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Optimal Weighted Convolution for Classification and Denosing Gated attention coding for training high-performance and efficient spiking neural networks

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Optimal Weighted Convolution for Classification and Denosing Deep CNN hyperparameter optimization algorithms for sensor-based human activity recognition

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Optimal Weighted Convolution for Classification and Denosing Artificial intelligence, machine learning and deep learning in advanced robotics, a review

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Optimal Weighted Convolution for Classification and Denosing Mobilenetv2: Inverted residuals and linear bottlenecks

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Optimal Weighted Convolution for Classification and Denosing Avoiding overfitting: A survey on regularization methods for convolutional neural networks

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Optimal Weighted Convolution for Classification and Denosing Very deep convolutional networks for large-scale image recognition

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Optimal Weighted Convolution for Classification and Denosing Efficientnet: Rethinking model scaling for convolutional neural networks

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Optimal Weighted Convolution for Classification and Denosing https://top500.org/lists/top500/2024/06/

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Optimal Weighted Convolution for Classification and Denosing Attention is all you need

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Optimal Weighted Convolution for Classification and Denosing A universal image quality index

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Optimal Weighted Convolution for Classification and Denosing Regularization of neural networks using dropconnect

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Optimal Weighted Convolution for Classification and Denosing Restormer: Efficient transformer for high-resolution image restoration

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Optimal Weighted Convolution for Classification and Denosing Hyperparameter optimization in cnn for learning-centered emotion recognition for intelligent tutoring systems

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Optimal Weighted Convolution for Classification and Denosing Improvement of generalization ability of deep CNN via implicit regularization in two-stage training process

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Optimal Weighted Convolution for Classification and Denosing Beyond a gaussian denoiser: Residual learning of deep CNN for image denoising

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Optimal Weighted Convolution for Classification and Denosing Fsim: A feature similarity index for image quality assessment

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Optimal Weighted Convolution for Classification and Denosing Ffdnet: Toward a fast and flexible solution for CNN -based image denoising

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Pith citing papers

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