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 2576–2600 of 10307 papers

TitleStatusHype
Brain Tumor Classification on MRI in Light of Molecular Markers—0
OmniXAS: A Universal Deep-Learning Framework for Materials X-ray Absorption SpectraCode0
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generationCode0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
On the universality of neural encodings in CNNs—0
How Effective is Pre-training of Large Masked Autoencoders for Downstream Earth Observation Tasks?—0
Student-Oriented Teacher Knowledge Refinement for Knowledge Distillation—0
Deep Hybrid Architecture for Very Low-Resolution Image Classification Using Capsule AttentionCode0
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge IntegrationCode0
Harmonizing knowledge Transfer in Neural Network with Unified Distillation—0
Meta-RTL: Reinforcement-Based Meta-Transfer Learning for Low-Resource Commonsense Reasoning—0
Transfer Learning in _1 Regularized Regression: Hyperparameter Selection Strategy based on Sharp Asymptotic Analysis—0
T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on an Assistant Task for a Target Task—0
Automated Segmentation and Analysis of Microscopy Images of Laser Powder Bed Fusion Melt Tracks—0
Jump Diffusion-Informed Neural Networks with Transfer Learning for Accurate American Option Pricing under Data Scarcity—0
Graph Pruning Based Spatial and Temporal Graph Convolutional Network with Transfer Learning for Traffic Prediction—0
Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised ModelsCode0
Speech Recognition Rescoring with Large Speech-Text Foundation Models—0
Unleashing the Potential of Synthetic Images: A Study on Histopathology Image ClassificationCode0
Transfer learning for financial data predictions: a systematic review—0
Online Multi-level Contrastive Representation Distillation for Cross-Subject fNIRS Emotion RecognitionCode0
Personalized Federated Learning via Backbone Self-Distillation—0
Machine Translation Advancements of Low-Resource Indian Languages by Transfer Learning—0
CON: Continual Object Navigation via Data-Free Inter-Agent Knowledge Transfer in Unseen and Unfamiliar Places—0
DSG-KD: Knowledge Distillation from Domain-Specific to General Language ModelsCode0
Show:102550
← PrevPage 104 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