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Small Data Image Classification
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Supervised image classification with tens to hundreds of labeled training examples.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Image Classification With Small Datasets: Overview and Benchmark
ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing
TorchXRayVision: A library of chest X-ray datasets and models
Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification
S2D2Net: An Improved Approach For Robust Steel Surface Defects Diagnosis With Small Sample Learning
Parametric Scattering Networks
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations
Auxiliary Learning by Implicit Differentiation
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models
PuzzLing Machines: A Challenge on Learning From Small Data
Ensemble long short-term memory (EnLSTM) network
ST$^2$: Small-data Text Style Transfer via Multi-task Meta-Learning
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense
Meta-Meta Classification for One-Shot Learning
Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response
Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data
On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems
Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset
Generative Latent Implicit Conditional Optimization when Learning from Small Sample
A Close Look at Deep Learning with Small Data
Deep Neural Review Text Interaction for Recommendation Systems
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
Adaptive Name Entity Recognition under Highly Unbalanced Data
Unbiased Mean Teacher for Cross-domain Object Detection
Rigid-Soft Interactive Learning for Robust Grasping
Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
Performance Analysis of Semi-supervised Learning in the Small-data Regime using VAEs
Better Classifier Calibration for Small Data Sets
Meta-learning for mixed linear regression
On Coresets for Support Vector Machines
On a scalable entropic breaching of the overfitting barrier in machine learning
Better Multi-class Probability Estimates for Small Data Sets
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
Identifying Table Structure in Documents using Conditional Generative Adversarial Networks
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