Papers Semi-Supervised Image Classification
“Semi-Supervised Image Classification” 태그가 달린 논문 169편 · 필터 해제
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
Effective convolutional neural networks are trained on large sets of labeled data. However, creating large labeled datasets is a very costly and time-consuming task. Semi-supervised learning uses unlabeled data to train …
Data AugmentationSemi-Supervised Image ClassificationImproved Techniques for Training GANs
We present a variety of new architectural features and training procedures that we apply to the generative adversarial networks (GANs) framework. We focus on two applications of GANs: semi-supervised learning, and the ge…
Conditional Image GenerationImage GenerationSemi-Supervised Image ClassificationUnsupervised High-level Feature Learning by Ensemble Projection for Semi-supervised Image Classification and Image Clustering
This paper investigates the problem of image classification with limited or no annotations, but abundant unlabeled data. The setting exists in many tasks such as semi-supervised image classification, image clustering, an…
ClassificationClusteringEnsemble LearningGeneral Classification+6Learning The Structure of Deep Convolutional Networks
In this work, we develop a novel method for automatically learning aspects of the structure of a deep model, in order to improve its performance, especially when labeled training data are scarce. We propose a new convo…
image-classificationImage ClassificationSemi-Supervised Image ClassificationSemi-Supervised Learning with Ladder Networks
We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to simultaneously minimize the sum of supervised and unsupervised cost functions by backpropagation, avoidi…
General ClassificationSemi-Supervised Image ClassificationStacked What-Where Auto-encoders
We present a novel architecture, the "stacked what-where auto-encoders" (SWWAE), which integrates discriminative and generative pathways and provides a unified approach to supervised, semi-supervised and unsupervised lea…
DecoderImage ClassificationSemi-Supervised Image ClassificationCURL: Co-trained Unsupervised Representation Learning for Image Classification
In this paper we propose a strategy for semi-supervised image classification that leverages unsupervised representation learning and co-training. The strategy, that is called CURL from Co-trained Unsupervised Representat…
ClassificationGeneral Classificationimage-classificationImage Classification+310,000+ Times Accelerated Robust Subset Selection (ARSS)
Subset selection from massive data with noised information is increasingly popular for various applications. This problem is still highly challenging as current methods are generally slow in speed and sensitive to outlie…
10-shot image generationAction RecognitionCollaborative FilteringFine-Grained Image Classification+20Comment on "Ensemble Projection for Semi-supervised Image Classification"
In a series of papers by Dai and colleagues [1,2], a feature map (or kernel) was introduced for semi- and unsupervised learning. This feature map is build from the output of an ensemble of classifiers trained without usi…
ClassificationGeneral Classificationimage-classificationImage Classification+1