SOTAVerified

Small Data Image Classification

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

Papers

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Showing 51–100 of 179 papers

TitleStatusHype
Deep Learning Approach for Very Similar Objects Recognition Application on Chihuahua and Muffin ProblemCode0
On Coresets for Support Vector MachinesCode0
Fragment Graphical Variational AutoEncoding for Screening Molecules with Small DataCode0
Performance Analysis of Semi-supervised Learning in the Small-data Regime using VAEsCode0
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled DataCode0
Deep learning for Chemometric and non-translational dataCode0
Capturing Structure Implicitly from Time-Series having Limited DataCode0
Deep Kernels with Probabilistic Embeddings for Small-Data LearningCode0
Improving Landmark Localization with Semi-Supervised Learning—0
Improving Transferability of Deep Neural Networks—0
Improving word alignment for low resource languages using English monolingual SRL—0
Incremental Learning of NCM Forests for Large-Scale Image Classification—0
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets—0
Interactive Evidence Detection: train state-of-the-art model out-of-domain or simple model interactively?—0
Interpretable Structure-Evolving LSTM—0
L1 logistic regression as a feature selection step for training stable classification trees for the prediction of severity criteria in imported malaria—0
Large-Scale Cox Process Inference using Variational Fourier Features—0
Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets—0
Latent-Variable Generative Models for Data-Efficient Text Classification—0
LDMNet: Low Dimensional Manifold Regularized Neural Networks—0
Learning like humans with Deep Symbolic Networks—0
Learning to Actively Learn Neural Machine Translation—0
Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds—0
Learning to Control Latent Representations for Few-Shot Learning of Named Entities—0
Learning with tree-based tensor formats—0
Less (Data) Is More: Why Small Data Holds the Key to the Future of Artificial Intelligence—0
Enhancing Simple Models by Exploiting What They Already Know—0
Lie Transform--based Neural Networks for Dynamics Simulation and Learning—0
Local Contrast Learning—0
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks—0
Lung CT Imaging Sign Classification through Deep Learning on Small Data—0
Massive Online Crowdsourced Study of Subjective and Objective Picture Quality—0
Maximum Likelihood Estimation for Single Linkage Hierarchical Clustering—0
Meta-learning for mixed linear regression—0
Meta Reinforcement Learning with Latent Variable Gaussian Processes—0
Modern Neural Networks Generalize on Small Data Sets—0
MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation—0
Multiphase flow prediction with deep neural networks—0
Multiple-gaze geometry: Inferring novel 3D locations from gazes observed in monocular video—0
A Distributionally Robust Optimization Method for Adversarial Multiple Kernel Learning—0
Nazr-CNN: Fine-Grained Classification of UAV Imagery for Damage Assessment—0
Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification—0
Novel quantitative indicators of digital ophthalmoscopy image quality—0
On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems—0
On a scalable entropic breaching of the overfitting barrier in machine learning—0
One-Shot Coresets: The Case of k-Clustering—0
Ordinal Constrained Binary Code Learning for Nearest Neighbor Search—0
Predicting Oral Disintegrating Tablet Formulations by Neural Network Techniques—0
Pretrained language model transfer on neural named entity recognition in Indonesian conversational texts—0
Promoting the Knowledge of Source Syntax in Transformer NMT Is Not Needed—0
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