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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 101–125 of 179 papers

TitleStatusHype
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers diseaseCode1
Fully Automatic Segmentation of Sublingual Veins from Retrained U-Net Model for Few Near Infrared Images—0
Synergy Effect between Convolutional Neural Networks and the Multiplicity of SMILES for Improvement of Molecular Prediction—0
Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets—0
Modern Neural Networks Generalize on Small Data Sets—0
Compact Representation of Uncertainty in Clustering—0
A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis—0
Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object DetectionCode1
Learning with tree-based tensor formats—0
An Infinite Parade of Giraffes: Expressive Augmentation and Complexity Layers for Cartoon DrawingCode0
DragonPaint: Rule based bootstrapping for small data with an application to cartoon coloring—0
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks—0
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation—0
Learning to Actively Learn Neural Machine Translation—0
Annotation of a Large Clinical Entity Corpus—0
The Fast and the Flexible: training neural networks to learn to follow instructions from small dataCode0
Multiple-gaze geometry: Inferring novel 3D locations from gazes observed in monocular video—0
Small Sample Learning in Big Data Era—0
A Semi-Supervised Data Augmentation Approach using 3D Graphical EnginesCode0
Improving Transferability of Deep Neural Networks—0
Deep semi-supervised segmentation with weight-averaged consistency targets—0
Bridging CNNs, RNNs, and Weighted Finite-State Machines—0
A Named Entity Recognition Shootout for German—0
Learning to Promote Saliency DetectorsCode0
OLÉ: Orthogonal Low-Rank Embedding - A Plug and Play Geometric Loss for Deep LearningCode0
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