文章总览 - 11
Pixel and region level information fusion in membership regularized fuzzy clustering for image segmentation
Pixel and region level information fusion in membership regularized fuzzy clustering for image segmentation

发表于Information Fusion 2023。

1
Forgery-aware Adaptive Learning with Vision Transformer for Generalized Face Forgery Detection
Forgery-aware Adaptive Learning with Vision Transformer for Generalized Face Forgery Detection

发表于TCSVT 2024。

2
Deep Adaptive Fuzzy Clustering for Evolutionary Unsupervised Representation Learning
Deep Adaptive Fuzzy Clustering for Evolutionary Unsupervised Representation Learning

发表于IEEE Transactions on Neural Networks and Learning Systems 2023,提出了DAFC来自动分组图像,得到的迭代优化问题可以通过小批量RMSprop和反向传播而不是SGD有效地解决,可以学习一个更聚类友好的瓶颈空间。

3
Fuzzy_Machine_Learning
Fuzzy_Machine_Learning

4
A survey on deep learning-based image forgery detection
A survey on deep learning-based image forgery detection

发表于Pattern Recognition 2023,基于深度学习的图像伪造检测综述。

5
SPL
SPL

6
Deep Fuzzy K-Means With Adaptive Loss and Entropy Regularization
Deep Fuzzy K-Means With Adaptive Loss and Entropy Regularization

发表于IEEE Transactions on Fuzzy Systems 2019,提出了深度模糊k-means(DFKM),具有加权自适应损失函数的FKM。

7
Robust deep fuzzy K-means clustering for image data
Robust deep fuzzy K-means clustering for image data

发表于JCR一区、CCF B类期刊的Pattern Recognition 2024,提出了一种新的边界引导图像篡改定位模型,该模型通过精心设计的注意力和对比学习机制充分利用被篡改区域的边界信息,利用拉普拉斯正则化方法对隶属度矩阵进行约束,使从相似样本中学习到的隶属度也相互关联,将自适应损失函数引入到统一的框架中,可以减少各种异常值的影响,有助于增强聚类的鲁棒性。

8
Robust deep k-means:An effective and simple method for data clustering
Robust deep k-means:An effective and simple method for data clustering

发表于PR 2021。

9
K-means clustering algorithms:A comprehensive review, variants analysis, and advances in the era of big data
K-means clustering algorithms:A comprehensive review, variants analysis, and advances in the era of big data

发表于Information Sciences 2023。

10