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Small Data Image Classification

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

Papers

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Showing 101–150 of 179 papers

TitleStatusHype
Spoofing and Anti-Spoofing with Wax Figure Faces—0
ST^2: Small-data Text Style Transfer via Multi-task Meta-Learning—0
Synergy Effect between Convolutional Neural Networks and the Multiplicity of SMILES for Improvement of Molecular Prediction—0
Synthesizing Deep Neural Network Architectures using Biological Synaptic Strength Distributions—0
Transfer Learning of fMRI Dynamics—0
United Statistical Algorithm, Small and Big Data: Future OF Statistician—0
VIBNN: Hardware Acceleration of Bayesian Neural Networks—0
Frankenstein: Learning Deep Face Representations using Small Data—0
Fully Automatic Segmentation of Sublingual Veins from Retrained U-Net Model for Few Near Infrared Images—0
Fully Convolutional Networks for Chip-wise Defect Detection Employing Photoluminescence Images—0
Generalizable prediction of academic performance from short texts on social media—0
High Dimensional Low Rank plus Sparse Matrix Decomposition—0
How biased are maximum entropy models?—0
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets—0
HydraMix: Multi-Image Feature Mixing for Small Data Image Classification—0
Identifying Table Structure in Documents using Conditional Generative Adversarial Networks—0
Improving Landmark Localization with Semi-Supervised Learning—0
Improving Transferability of Deep Neural Networks—0
Improving word alignment for low resource languages using English monolingual SRL—0
Incremental Learning of NCM Forests for Large-Scale Image Classification—0
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets—0
Interactive Evidence Detection: train state-of-the-art model out-of-domain or simple model interactively?—0
Interpretable Structure-Evolving LSTM—0
L1 logistic regression as a feature selection step for training stable classification trees for the prediction of severity criteria in imported malaria—0
Large-Scale Cox Process Inference using Variational Fourier Features—0
Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets—0
Latent-Variable Generative Models for Data-Efficient Text Classification—0
LDMNet: Low Dimensional Manifold Regularized Neural Networks—0
Learning like humans with Deep Symbolic Networks—0
Learning to Actively Learn Neural Machine Translation—0
Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds—0
Learning to Control Latent Representations for Few-Shot Learning of Named Entities—0
Learning with tree-based tensor formats—0
Less (Data) Is More: Why Small Data Holds the Key to the Future of Artificial Intelligence—0
Enhancing Simple Models by Exploiting What They Already Know—0
Lie Transform--based Neural Networks for Dynamics Simulation and Learning—0
Local Contrast Learning—0
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks—0
Estimating uncertainty of earthquake rupture using Bayesian neural networkCode0
Fragment Graphical Variational AutoEncoding for Screening Molecules with Small DataCode0
S2D2Net: An Improved Approach For Robust Steel Surface Defects Diagnosis With Small Sample LearningCode0
CuMF_SGD: Fast and Scalable Matrix FactorizationCode0
Stochastic Function Norm Regularization of Deep NetworksCode0
Comparison of Deep learning models on time series forecasting : a case study of Dissolved Oxygen PredictionCode0
Generative Modeling for Small-Data Object DetectionCode0
Global Autoregressive Models for Data-Efficient Sequence LearningCode0
Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASRCode0
Harnessing the Power of Infinitely Wide Deep Nets on Small-data TasksCode0
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential EquationsCode0
Performance Analysis of Semi-supervised Learning in the Small-data Regime using VAEsCode0
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