Search Results for author: Hong Peng

Found 9 papers, 1 papers with code

Less is more: Ensemble Learning for Retinal Disease Recognition Under Limited Resources

no code implementations15 Feb 2024 Jiahao Wang, Hong Peng, Shengchao Chen, Sufen Ren

This approach establishes a robust model even when confronted with limited labeled data, eliminating the need for an extensive array of parameters, as required in learning from scratch.

Decision Making Ensemble Learning

Multi-stages attention Breast cancer classification based on nonlinear spiking neural P neurons with autapses

no code implementations20 Dec 2023 Bo Yang, Hong Peng, Xiaohui Luo, Jun Wang

Downsampling in deep networks may lead to loss of information, so for compensating the detail and edge information and allowing convolutional neural networks to pay more attention to seek the lesion region, we propose a multi-stages attention architecture based on NSNP neurons with autapses.

SAMN: A Sample Attention Memory Network Combining SVM and NN in One Architecture

no code implementations25 Sep 2023 Qiaoling Yang, Linkai Luo, Haoyu Zhang, Hong Peng, Ziyang Chen

To address this, we propose a sample attention memory network (SAMN) that effectively combines SVM and NN by incorporating sample attention module, class prototypes, and memory block to NN.

MaxMin-L2-SVC-NCH: A Novel Approach for Support Vector Classifier Training and Parameter Selection

no code implementations14 Jul 2023 Linkai Luo, Qiaoling Yang, Hong Peng, Yiding Wang, Ziyang Chen

We first formulate the training and parameter selection of SVC as a minimax optimization problem named as MaxMin-L2-SVC-NCH, in which the minimization problem is an optimization problem of finding the closest points between two normal convex hulls (L2-SVC-NCH) while the maximization problem is an optimization problem of finding the optimal Gaussian kernel parameters.

One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstruction

1 code implementation15 Aug 2022 Hong Peng, Chen Jiang, Jing Cheng, Minghui Zhang, Shanshan Wang, Dong Liang, Qiegen Liu

At the prior learning stage, we first construct a large Hankel matrix from k-space data, then extract multiple structured k-space patches from the large Hankel matrix to capture the internal distribution among different patches.

Fronthaul Compression and Passive Beamforming Design for Intelligent Reflecting Surface-aided Cloud Radio Access Networks

no code implementations25 Feb 2021 Yu Zhang, Xuelu Wu, Hong Peng, Caijun Zhong, Xiaoming Chen

This letter studies a cloud radio access network (C-RAN) with multiple intelligent reflecting surfaces (IRS) deployed between users and remote radio heads (RRH).


Integrating Tensor Similarity to Enhance Clustering Performance

no code implementations10 May 2019 Hong Peng, Yu Hu, Jiazhou Chen, Hai-Yan Wang, Yang Li, Hongmin Cai

The performance of most the clustering methods hinges on the used pairwise affinity, which is usually denoted by a similarity matrix.


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