HyperAI超神経

ホームニュース最新論文チュートリアルデータセット百科事典 SOTA LLMモデル GPU ランキング学会

サイトについて

日本語

HyperAI超神経

Image Clustering On Tiny Imagenet

評価指標

Accuracy

NMI

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名	Accuracy	NMI	Paper Title	Repository
DAC	0.066	0.190	Deep Adaptive Image Clustering
MMDC	0.119	0.274	Multi-Modal Deep Clustering: Unsupervised Partitioning of Images
GAN	0.041	0.135	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
PRO-DSC	0.698	0.805	Exploring a Principled Framework For Deep Subspace Clustering
VAE	0.036	0.113	Auto-Encoding Variational Bayes
SPICE	0.305	0.449	SPICE: Semantic Pseudo-labeling for Image Clustering
ITAE	0.6823	0.8178	Improving Image Clustering with Artifacts Attenuation via Inference-Time Attention Engineering	-
DEC	0.037	0.115	Unsupervised Deep Embedding for Clustering Analysis
CC	0.14	0.34	Contrastive Clustering
C3	0.141	0.335	C3: Cross-instance guided Contrastive Clustering
IMC-SwAV (Best)	0.282	0.526	Information Maximization Clustering via Multi-View Self-Labelling
DCCM	0.108	0.224	Deep Comprehensive Correlation Mining for Image Clustering
JULE	0.033	0.102	Joint Unsupervised Learning of Deep Representations and Image Clusters
IMC-SwAV (Avg+-)	0.279	0.485	Information Maximization Clustering via Multi-View Self-Labelling

0 of 14 row(s) selected.