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 8251–8300 of 10307 papers

TitleStatusHype
Automatic segmentation of texts into units of meaning for reading assistance—0
Automatic Sleep Stage Classification with Cross-modal Self-supervised Features from Deep Brain Signals—0
Automatic Speech Recognition for Sanskrit with Transfer Learning—0
Automatic Speech Recognition using Advanced Deep Learning Approaches: A survey—0
Automatic Tuberculosis and COVID-19 cough classification using deep learning—0
Automatic Wayang Ontology Construction using Relation Extraction from Free Text—0
Automating the Surveillance of Mosquito Vectors from Trapped Specimens Using Computer Vision Techniques—0
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning—0
AutoML Systems For Medical Imaging—0
Autonomous crater detection on asteroids using a fully-convolutional neural network—0
Autonomous Extraction of a Hierarchical Structure of Tasks in Reinforcement Learning, A Sequential Associate Rule Mining Approach—0
Autonomous learning of multiple, context-dependent tasks—0
Autonomous Vehicle Fleet Coordination With Deep Reinforcement Learning—0
AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning—0
Auto-Transfer: Learning to Route Transferable Representations—0
AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data—0
Auxiliary Input in Training: Incorporating Catheter Features into Deep Learning Models for ECG-Free Dynamic Coronary Roadmapping—0
A View Independent Classification Framework for Yoga Postures—0
A Vision-based Solution for Track Misalignment Detection—0
A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models—0
A visual encoding model based on deep neural networks and transfer learning—0
Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data—0
A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification—0
A Zero-Shot Generalization Framework for LLM-Driven Cross-Domain Sequential Recommendation—0
A Zero-Shot Learning Approach for Ephemeral Gully Detection from Remote Sensing using Vision Language Models—0
BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs—0
Baby Physical Safety Monitoring in Smart Home Using Action Recognition System—0
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition—0
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models—0
Backdoor Attacks Against Deep Learning Systems in the Physical World—0
Background-Foreground Segmentation for Interior Sensing in Automotive Industry—0
BactInt: A domain driven transfer learning approach and a corpus for extracting inter-bacterial interactions from biomedical text—0
BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models—0
Bailong: Bilingual Transfer Learning based on QLoRA and Zip-tie Embedding—0
Balanced Distribution Adaptation for Transfer Learning—0
Balanced Multi-Factor In-Context Learning for Multilingual Large Language Models—0
Balanced Multi-modal Federated Learning via Cross-Modal Infiltration—0
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime—0
Balancing Accuracy and Training Time in Federated Learning for Violence Detection in Surveillance Videos: A Study of Neural Network Architectures—0
Balancing Data through Data Augmentation Improves the Generality of Transfer Learning for Diabetic Retinopathy Classification—0
Balancing Exploration and Exploitation in LLM using Soft RLLF for Enhanced Negation Understanding—0
BANANA at WNUT-2020 Task 2: Identifying COVID-19 Information on Twitter by Combining Deep Learning and Transfer Learning Models—0
Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets—0
Banana Sub-Family Classification and Quality Prediction using Computer Vision—0
BarlowTwins-CXR : Enhancing Chest X-Ray abnormality localization in heterogeneous data with cross-domain self-supervised learning—0
Baselines for Reinforcement Learning in Text Games—0
Basic Level Categorization Facilitates Visual Object Recognition—0
Basis Scaling and Double Pruning for Efficient Inference in Network-Based Transfer Learning—0
BayesAdapter: enhanced uncertainty estimation in CLIP few-shot adaptation—0
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori—0
Show:102550
← PrevPage 166 of 207Next →
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