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Small Data Image Classification

24 papers with code · Computer Vision

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

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Learning What and Where to Transfer

15 May 2019jindongwang/transferlearning

To address the issue, we propose a novel transfer learning approach based on meta-learning that can automatically learn what knowledge to transfer from the source network to where in the target network.

META-LEARNING SMALL DATA IMAGE CLASSIFICATION TRANSFER LEARNING

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

21 Nov 2018pfjaeger/medicaldetectiontoolkit

The proposed architecture recaptures discarded supervision signals by complementing object detection with an auxiliary task in the form of semantic segmentation without introducing the additional complexity of previously proposed two-stage detectors.

MEDICAL OBJECT DETECTION SEMANTIC SEGMENTATION SMALL DATA IMAGE CLASSIFICATION

Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR

29 May 2019fgnt/pb_chime5

In this paper, we present Hitachi and Paderborn University's joint effort for automatic speech recognition (ASR) in a dinner party scenario.

SMALL DATA IMAGE CLASSIFICATION SPEECH ENHANCEMENT SPEECH RECOGNITION

Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations

2 Aug 2017maziarraissi/HPM

While there is currently a lot of enthusiasm about "big data", useful data is usually "small" and expensive to acquire.

GAUSSIAN PROCESSES SMALL DATA IMAGE CLASSIFICATION

Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

ICLR 2020 LeoYu/neural-tangent-kernel-UCI

On VOC07 testbed for few-shot image classification tasks on ImageNet with transfer learning (Goyal et al., 2019), replacing the linear SVM currently used with a Convolutional NTK SVM consistently improves performance.

FEW-SHOT IMAGE CLASSIFICATION SMALL DATA IMAGE CLASSIFICATION TRANSFER LEARNING

OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning

5 Dec 2017jlezama/OrthogonalLowrankEmbedding

Deep neural networks trained using a softmax layer at the top and the cross-entropy loss are ubiquitous tools for image classification.

METRIC LEARNING OBJECT RECOGNITION SMALL DATA IMAGE CLASSIFICATION

On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location

16 Mar 2020oskyhn/CNNs-Without-Borders

In this paper we challenge the common assumption that convolutional layers in modern CNNs are translation invariant.

SMALL DATA IMAGE CLASSIFICATION VIDEO CLASSIFICATION

SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery

12 Nov 2019DSPsleeporg/smiles-transformer

Inspired by Transformer and pre-trained language models from natural language processing, SMILES Transformer learns molecular fingerprints through unsupervised pre-training of the sequence-to-sequence language model using a huge corpus of SMILES, a text representation system for molecules.

DRUG DISCOVERY LANGUAGE MODELLING SMALL DATA IMAGE CLASSIFICATION

Learning to Promote Saliency Detectors

CVPR 2018 zengxianyu/lps

The categories and appearance of salient objects vary from image to image, therefore, saliency detection is an image-specific task.

SALIENCY DETECTION SMALL DATA IMAGE CLASSIFICATION ZERO-SHOT LEARNING