SOTAVerified

Small Data Image Classification

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

Papers

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Showing 1–25 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
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep LearningCode1
Tune It or Don't Use It: Benchmarking Data-Efficient Image ClassificationCode1
Rigid-Soft Interactive Learning for Robust GraspingCode1
Ensemble long short-term memory (EnLSTM) networkCode1
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial LocationCode1
Image Classification With Small Datasets: Overview and BenchmarkCode1
Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object DetectionCode1
Analysis of Social Media Data using Multimodal Deep Learning for Disaster ResponseCode1
Finding Covid-19 from Chest X-rays using Deep Learning on a Small DatasetCode1
Parametric Scattering NetworksCode1
Unbiased Mean Teacher for Cross-domain Object DetectionCode1
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers diseaseCode1
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
ChimeraMix: Image Classification on Small Datasets via Masked Feature MixingCode1
Generative Latent Implicit Conditional Optimization when Learning from Small SampleCode1
Global Autoregressive Models for Data-Efficient Sequence LearningCode0
An Infinite Parade of Giraffes: Expressive Augmentation and Complexity Layers for Cartoon DrawingCode0
Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASRCode0
Fragment Graphical Variational AutoEncoding for Screening Molecules with Small DataCode0
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational InferenceCode0
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data AnnotationsCode0
Generative Modeling for Small-Data Object DetectionCode0
Harnessing the Power of Infinitely Wide Deep Nets on Small-data TasksCode0
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