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5 results for “near-duplicates”
Training on test data: Removing near duplicates in Fashion-MNISTcs.LG

This paper removes near-duplicates from Fashion-MNIST to improve testing accuracy.

problem Near-duplicate images in Fashion-MNIST increase testing accuracy, reducing dataset quality.
method Identified and removed near-duplicate images between training and testing sets.
result Improved dataset quality for better testing accuracy in machine learning models.
Fashion-MNISTnear-duplicatesdataset qualitymachine learning
2019-06-19abs ↗pdf ↗
Benchmarking unsupervised near-duplicate image detectioncs.CV

This study benchmarks deep learning for unsupervised near-duplicate image detection.

problem Detecting near-duplicates in large image datasets with high specificity.
method Binary classification using Receiver Operating Curve (ROC) for comparison of different descriptors.
result Fine-tuning deep convolutional networks generally outperforms off-the-shelf features, with best performance on MFND dataset.
unsupervised detectionnear-duplicatesdeep learningconvolutional neural networksbinary classification
2019-07-03abs ↗pdf ↗
ProbMinHash -- A Class of Locality-Sensitive Hash Algorithms for the (Probability) Jaccard Similaritycs.DS

ProbMinHash improves Jaccard similarity hashing for big data applications.

problem Efficiently estimating set similarities in big data with weighted elements.
method Locality-sensitive hash algorithms that calculate signatures collectively.
result Significantly faster than the original approach, with improved estimation error.
Locality-sensitive hashingJaccard similarityBig dataProbabilityNear-duplicate detection
2019-11-02abs ↗pdf ↗