SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9201–9225 of 10307 papers

TitleStatusHype
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging—0
Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attention—0
CNN-LSTM and Transfer Learning Models for Malware Classification based on Opcodes and API Calls—0
CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation—0
Coarse-To-Fine And Cross-Lingual ASR Transfer—0
Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network—0
CoCo DistillNet: a Cross-layer Correlation Distillation Network for Pathological Gastric Cancer Segmentation—0
CoCoNet: A Collaborative Convolutional Network—0
Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI—0
Boosting Deep Transfer Learning for COVID-19 Classification—0
Boosting Deep Face Recognition via Disentangling Appearance and Geometry—0
Code-Mixed Text to Speech Synthesis under Low-Resource Constraints—0
Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation—0
CoDo: Contrastive Learning with Downstream Background Invariance for Detection—0
Coefficient Shape Transfer Learning for Functional Linear Regression—0
Coevo: a collaborative design platform with artificial agents—0
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform—0
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning—0
Maze Learning using a Hyperdimensional Predictive Processing Cognitive Architecture—0
RailSem19: A Dataset for Semantic Rail Scene Understanding—0
Cognitive Learning-Aided Multi-Antenna Communications—0
Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data—0
The Joy of Neural Painting—0
Coherence Modeling Improves Implicit Discourse Relation Recognition—0
Coherent and Consistent Relational Transfer Learning with Autoencoders—0
Show:102550
← PrevPage 369 of 413Next →
All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified