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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 1–50 of 179 papers

TitleStatusHype
TorchXRayVision: A library of chest X-ray datasets and modelsCode2
Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small dataCode2
ChimeraMix: Image Classification on Small Datasets via Masked Feature MixingCode1
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers diseaseCode1
Ensemble long short-term memory (EnLSTM) networkCode1
Generative Latent Implicit Conditional Optimization when Learning from Small SampleCode1
Analysis of Social Media Data using Multimodal Deep Learning for Disaster ResponseCode1
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep LearningCode1
Finding Covid-19 from Chest X-rays using Deep Learning on a Small DatasetCode1
Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object DetectionCode1
Parametric Scattering NetworksCode1
Unbiased Mean Teacher for Cross-domain Object DetectionCode1
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial LocationCode1
Rigid-Soft Interactive Learning for Robust GraspingCode1
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
Tune It or Don't Use It: Benchmarking Data-Efficient Image ClassificationCode1
Image Classification With Small Datasets: Overview and BenchmarkCode1
Randomly Projected Additive Gaussian Processes for RegressionCode0
S2D2Net: An Improved Approach For Robust Steel Surface Defects Diagnosis With Small Sample LearningCode0
On Coresets for Support Vector MachinesCode0
OLÉ: Orthogonal Low-Rank Embedding - A Plug and Play Geometric Loss for Deep LearningCode0
OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep LearningCode0
Performance Analysis of Semi-supervised Learning in the Small-data Regime using VAEsCode0
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational InferenceCode0
SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug DiscoveryCode0
Learning What and Where to TransferCode0
An Infinite Parade of Giraffes: Expressive Augmentation and Complexity Layers for Cartoon DrawingCode0
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled DataCode0
Learning to Promote Saliency DetectorsCode0
Meta-Meta Classification for One-Shot LearningCode0
Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and SummarisationCode0
Data Structures & Algorithms for Exact Inference in Hierarchical ClusteringCode0
MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender SystemsCode0
A Semi-Supervised Data Augmentation Approach using 3D Graphical EnginesCode0
Harnessing the Power of Infinitely Wide Deep Nets on Small-data TasksCode0
Capturing Structure Implicitly from Time-Series having Limited DataCode0
Generative Modeling for Small-Data Object DetectionCode0
Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASRCode0
Global Autoregressive Models for Data-Efficient Sequence LearningCode0
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential EquationsCode0
Comparison of Deep learning models on time series forecasting : a case study of Dissolved Oxygen PredictionCode0
Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systemsCode0
Estimating uncertainty of earthquake rupture using Bayesian neural networkCode0
CuMF_SGD: Fast and Scalable Matrix FactorizationCode0
Auxiliary Learning by Implicit DifferentiationCode0
Data-efficient Neural Text Compression with Interactive LearningCode0
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data AnnotationsCode0
Deep Learning Approach for Very Similar Objects Recognition Application on Chihuahua and Muffin ProblemCode0
Deep learning for Chemometric and non-translational dataCode0
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regimeCode0
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