SOTAVerified

Small Data Image Classification

Supervised image classification with tens to hundreds of labeled training examples.

Papers

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Showing 51–75 of 179 papers

TitleStatusHype
Learning What and Where to TransferCode0
High-risk learning: acquiring new word vectors from tiny dataCode0
Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity DataCode0
Harnessing the Power of Infinitely Wide Deep Nets on Small-data TasksCode0
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential EquationsCode0
Meta-Meta Classification for One-Shot LearningCode0
Stochastic Function Norm Regularization of Deep NetworksCode0
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regimeCode0
FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition—0
Evaluating the Consistency of Word Embeddings from Small Data—0
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning—0
Beyond Fine Tuning: A Modular Approach to Learning on Small Data—0
Annotation of a Large Clinical Entity Corpus—0
Ensemble and Reranking: Using Multiple Models in the NICT-2 Neural Machine Translation System at WAT2017—0
Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization—0
Better Multi-class Probability Estimates for Small Data Sets—0
Effect of Activation Functions on the Training of Overparametrized Neural Nets—0
DragonPaint: Rule based bootstrapping for small data with an application to cartoon coloring—0
Better Classifier Calibration for Small Data Sets—0
A database for face presentation attack using wax figure faces—0
Do we still need fuzzy classifiers for Small Data in the Era of Big Data?—0
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models—0
Bayesian Learning for Neural Dependency Parsing—0
Deep semi-supervised segmentation with weight-averaged consistency targets—0
Bayesian inverse regression for dimension reduction with small datasets—0
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