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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 26–50 of 179 papers

TitleStatusHype
Bayesian Learning for Neural Dependency Parsing—0
Better Classifier Calibration for Small Data Sets—0
Better Multi-class Probability Estimates for Small Data Sets—0
Beyond Fine Tuning: A Modular Approach to Learning on Small Data—0
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning—0
FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition—0
Facial Expression Recognition Using a Hybrid CNN-SIFT Aggregator—0
DragonPaint: Rule based bootstrapping for small data with an application to cartoon coloring—0
A Close Look at Deep Learning with Small Data—0
Effect of Activation Functions on the Training of Overparametrized Neural Nets—0
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models—0
A simple efficient density estimator that enables fast systematic search—0
Compact Representation of Uncertainty in Clustering—0
Analysis of PCA Algorithms in Distributed Environments—0
Do we still need fuzzy classifiers for Small Data in the Era of Big Data?—0
Automated detection of oral pre-cancerous tongue lesions using deep learning for early diagnosis of oral cavity cancer—0
Competing Models—0
Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization—0
Credal Model Averaging for classification: representing prior ignorance and expert opinions—0
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense—0
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation—0
Deep Kernel Learning via Random Fourier Features—0
Active Image Synthesis for Efficient Labeling—0
Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets—0
CD2 : Combined Distances of Contrast Distributions for the Assessment of Perceptual Quality of Image Processing—0
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