HyperAI
Startseite
Neuigkeiten
Neueste Forschungsarbeiten
Tutorials
Datensätze
Wiki
SOTA
LLM-Modelle
GPU-Rangliste
Veranstaltungen
Suche
Über
Deutsch
HyperAI
Toggle sidebar
Seite durchsuchen…
⌘
K
Startseite
SOTA
Incremental Learning
Incremental Learning On Cifar 100 50 Classes 3
Incremental Learning On Cifar 100 50 Classes 3
Metriken
Average Incremental Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Average Incremental Accuracy
Paper Title
Repository
UCIR (CNN)*
63.42
Learning a Unified Classifier Incrementally via Rebalancing
PODNet (CNN)
64.83
PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning
TCIL-Lite
74.30
Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning
CCIL-SD
67.17
Essentials for Class Incremental Learning
TCIL
74.88
Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning
FOSTER
69.46
FOSTER: Feature Boosting and Compression for Class-Incremental Learning
PPCA-SWSL
-
Scalable Learning with Incremental Probabilistic PCA
UCIR (NME)*
63.12
Learning a Unified Classifier Incrementally via Rebalancing
DER(Modified Res-32)
67.60
DER: Dynamically Expandable Representation for Class Incremental Learning
PPCA-CLIP
-
Scalable Learning with Incremental Probabilistic PCA
D3Former
72.23
D3Former: Debiased Dual Distilled Transformer for Incremental Learning
iCaRL*
57.17
iCaRL: Incremental Classifier and Representation Learning
BiC
56.86
Large Scale Incremental Learning
DER(Standard ResNet-18)
72.60
DER: Dynamically Expandable Representation for Class Incremental Learning
RMM (Modified ResNet-32)
68.86
RMM: Reinforced Memory Management for Class-Incremental Learning
0 of 15 row(s) selected.
Previous
Next