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

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Showing 2551–2575 of 10307 papers

TitleStatusHype
Depression and Anxiety Prediction Using Deep Language Models and Transfer Learning—0
Behavior Priors for Efficient Reinforcement Learning—0
An Optimized Ensemble Deep Learning Model For Brain Tumor Classification—0
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages—0
Beam Selection in ISAC using Contextual Bandit with Multi-modal Transformer and Transfer Learning—0
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian—0
An Efficient Deep Learning-based approach for Recognizing Agricultural Pests in the Wild—0
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays—0
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian—0
BD-KD: Balancing the Divergences for Online Knowledge Distillation—0
A comprehensive study on Blood Cancer detection and classification using Convolutional Neural Network—0
BCNet: A Deep Convolutional Neural Network for Breast Cancer Grading—0
Bazinga! A Dataset for Multi-Party Dialogues Structuring—0
Addressing the Challenges of Cross-Lingual Hate Speech Detection—0
De-novo Chemical Reaction Generation by Means of Temporal Convolutional Neural Networks—0
Dense Classification and Implanting for Few-Shot Learning—0
Bayesian Transfer Reinforcement Learning with Prior Knowledge Rules—0
An Effective Scheme for Maize Disease Recognition based on Deep Networks—0
Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning—0
Bayesian Transfer Learning—0
An Effective End-to-End Solution for Multimodal Action Recognition—0
Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning—0
Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems—0
Addressing materials' microstructure diversity using transfer learning—0
Bayesian Optimization of Bilevel Problems—0
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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