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 9601–9650 of 10307 papers

TitleStatusHype
AMNet: Memorability Estimation with AttentionCode0
Assessment of Breast Cancer Histology using Densely Connected Convolutional Networks—0
Towards Deep Cellular Phenotyping in Placental HistologyCode0
Impact of ultrasound image reconstruction method on breast lesion classification with neural transfer learning—0
Bringing Cartoons to Life: Towards Improved Cartoon Face Detection and Recognition SystemsCode0
Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars—0
Boosting Handwriting Text Recognition in Small Databases with Transfer LearningCode0
Multi-lingual neural title generation for e-Commerce browse pages—0
StarCraft Micromanagement with Reinforcement Learning and Curriculum Transfer LearningCode0
DOCK: Detecting Objects by transferring Common-sense Knowledge—0
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural NetworksCode1
Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation—0
Forecasting Future Humphrey Visual Fields Using Deep LearningCode0
Can Multisensory Cues in VR Help Train Pattern Recognition to Citizen Scientists?—0
Webly Supervised Learning for Skin Lesion Classification—0
HOUDINI: Lifelong Learning as Program SynthesisCode0
Class Subset Selection for Transfer Learning using Submodularity—0
Reusing Neural Speech Representations for Auditory Emotion Recognition—0
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task LearningCode0
AI Blue Book: Vehicle Price Prediction using Visual FeaturesCode0
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images—0
PIMKL: Pathway Induced Multiple Kernel Learning—0
Universal Sentence EncoderCode1
Adversarial Network Compression—0
Learning Deep Representations with Probabilistic Knowledge Transfer—0
Deep Learning Object Detection Methods for Ecological Camera Trap Data—0
Efficient parametrization of multi-domain deep neural networksCode1
Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation—0
Domain transfer convolutional attribute embedding—0
DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes—0
Importance Weighted Adversarial Nets for Partial Domain Adaptation—0
Feature Transfer Learning for Deep Face Recognition with Under-Represented Data—0
Learning the Localization Function: Machine Learning Approach to Fingerprinting Localization—0
Domain Adaptation with Randomized Expectation MaximizationCode0
Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal PatternsCode0
Diagnostic Classification Of Lung Nodules Using 3D Neural NetworksCode0
Joint Recognition of Handwritten Text and Named Entities with a Neural End-to-end Model—0
Deep learning for affective computing: text-based emotion recognition in decision support—0
Transferable Pedestrian Motion Prediction Models at Intersections—0
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled DataCode0
Coregionalised Locomotion Envelopes - A Qualitative Approach—0
General-Purpose Deep Point Cloud Feature ExtractorCode0
Transfer Learning with Neural AutoML—0
Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification—0
LSTD: A Low-Shot Transfer Detector for Object DetectionCode0
Knowledge Transfer with Jacobian Matching—0
Gotta Adapt 'Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the WildCode0
Classification of breast cancer histology images using transfer learning—0
Attention-Aware Generative Adversarial Networks (ATA-GANs)—0
Discriminative Label Consistent Domain Adaptation—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