Deep Semi-NMF (DSN), which learns hierarchical representations by stacking multiple layers Semi-NMF, shows competitive performance in unsupervised data analysis. However, the features learned from DSN always lack of representativity and discriminativity. In this paper, we build a novel Deep Semi-...
DeepSemi-NMF源代码过期**邮递 上传4.12 KB 文件格式 m Deep-Semi-NM 该代码是用matlab编写的,为深度半非负矩阵分解算法,用于人脸识别的。点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 判断一个数是否为素数.txt 2025-04-01 17:15:04 积分:1 判断一个数是否为素数.txt 2025-04-01 17:23:...
作者:傅卓军,胡政,邓阳君,龙陈锋,朱幸辉 关键词:图像分割 苹果斑点落叶病 异常检测 深度半非负矩阵分解 马氏距离 DOI: 10.12133/j.smartag.SA202409001 年份: 2024 收藏 引用 批量引用 报错 分享 全部来源 求助全文 iAcademic 来源期刊 智慧农业(中英文) 2025-01-16 站内活动 ...
DeepSemiNMF.ziplo**ly 上传2.51 MB 文件格式 zip Theano-based implementation of Deep Semi-NMF. 点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 变分自编码器(VAE)进阶 2025-03-31 13:38:19 积分:1 nodebpm 2025-03-31 13:37:22 积分:1 ...
Unsupervised and semi-supervised learn- ing with categorical generative adversarial networks. arXiv preprint arXiv:1511.06390, 2015. 3 [45] G. Trigeorgis, K. Bousmalis, S. Zafeiriou, and B. Schuller. A deep semi-nmf model for learning hidden representations. In International Conference on ...
DCCA learns the data of each view, fuses information of different views into a common consensus representation and then conducts some clustering approaches (such as k-means) on the learned representation; DMF-MVC uses a deep semi-NMF structure to capture the nonlinear structure and generated a ...
We compare the proposed RDKM on 12 benchmark datasets against six baselines: the standard k-means [8], NMF [32], Orthogonal NMF (ONMF) [30], Semi-NMF (SNMF) [38], l2,1-NMF [36] and the deep Semi-NMF (DeepSNMF) [34]. Conclusion In this paper, we introduced a robust deep k...
K NMF GNMF nsNMF Deep Semi-NMF Deep nsNMF NMF GNMF nsNMF Deep Semi-NMF Deep nsNMF 2 85.00 89.00 85.00 86.00 95.00 51.05 59.73 51.05 53.85 76.10 3 80.00 81.00 83.33 81.00 93.33 64.90 70.97 74.03 65.60 84.11 4 69.25 77.15 73.50 72.25 80.00 56.72 65.26 65.10 63.78 69.25 5 74.60 74.00 75....
developed NMFDR, which is a complex drug-disease interaction network that integrates drug-disease associations along with disease and drug similarities, predicting the scores for unidentified drug-disease pairs was made possible by an advanced non-negative matrix factorization method [15]. Wang et al...
In this section, we briefly review semi-NMF. Given a nonnegative data matrix X=[x1,x2,⋯,xn]∈Rd×n, NMF aims to find two matrices Z∈ Rd× k and H∈ Rk× n which minimize the Proposed method In this section, we briefly introduce our proposed algorithm SDDMF. We start with ...