Similarity learning
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A Decade Survey of Content Based Image Retrieval Using Deep Learning Open
The content based image retrieval aims to find the similar images from a\nlarge scale dataset against a query image. Generally, the similarity between\nthe representative features of the query image and dataset images is used to\nrank the …
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Graph Matching Networks for Learning the Similarity of Graph Structured Objects Open
This paper addresses the challenging problem of retrieval and matching of graph structured objects, and makes two key contributions. First, we demonstrate how Graph Neural Networks (GNN), which have emerged as an effective model for variou…
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Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination Open
Neural net classifiers trained on data with annotated class labels can also capture apparent visual similarity among categories without being directed to do so. We study whether this observation can be extended beyond the conventional doma…
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Learned Multi-patch Similarity Open
© 2017 IEEE. Estimating a depth map from multiple views of a scene is a fundamental task in computer vision. As soon as more than two viewpoints are available, one faces the very basic question how to measure similarity across >2 image pat…
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Collaborative Similarity Embedding for Recommender Systems Open
We present collaborative similarity embedding (CSE), a unified framework that exploits comprehensive collaborative relations available in a user-item bipartite graph for representation learning and recommendation. In the proposed framework…
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Graph Matching Networks for Learning the Similarity of Graph Structured Objects Open
This paper addresses the challenging problem of retrieval and matching of graph structured objects, and makes two key contributions. First, we demonstrate how Graph Neural Networks (GNN), which have emerged as an effective model for variou…
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Deep graph similarity learning: a survey Open
In many domains where data are represented as graphs, learning a similarity metric among graphs is considered a key problem, which can further facilitate various learning tasks, such as classification, clustering, and similarity search. Re…
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Large Scale Similarity Learning Using Similar Pairs for Person Verification Open
In this paper, we propose a novel similarity measure and then introduce an efficient strategy to learn it by using only similar pairs for person verification. Unlike existing metric learning methods, we consider both the difference and com…
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Adaptive Collaborative Similarity Learning for Unsupervised Multi-view Feature Selection Open
In this paper, we investigate the research problem of unsupervised multi-view feature selection. Conventional solutions first simply combine multiple pre-constructed view-specific similarity structures into a collaborative similarity struc…
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Image similarity using Deep CNN and Curriculum Learning Open
Image similarity involves fetching similar looking images given a reference image. Our solution called SimNet, is a deep siamese network which is trained on pairs of positive and negative images using a novel online pair mining strategy in…
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Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking Open
Accurately ranking images and multimedia objects are of paramount relevance in many retrieval and learning tasks. Manifold learning methods have been investigated for ranking mainly due to their capacity of taking into account the intrinsi…
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Geometry-Aware Similarity Learning on SPD Manifolds for Visual Recognition Open
Symmetric positive definite (SPD) matrices have been employed for data representation in many visual recognition tasks. The success is mainly attributed to learning discriminative SPD matrices encoding the Riemannian geometry of the underl…
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Enhanced-RCNN: An Efficient Method for Learning Sentence Similarity Open
Learning sentence similarity is a fundamental research topic and has been explored using various deep learning methods recently. In this paper, we further propose an enhanced recurrent convolutional neural network (Enhanced-RCNN) model for…
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P<span>eax</span>: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning Open
We present P eax , a novel feature‐based technique for interactive visual pattern search in sequential data, like time series or data mapped to a genome sequence. Visually searching for patterns by similarity is often challenging because o…
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Hybrid Graph Convolutional Network for Semi-Supervised Retinal Image Classification Open
Diabetic Retinopathy (DR) causes a significant health threat to the patient's vision with diabetic disease, which may result in blindness in severe situations. Various automatic DR diagnosis models have been proposed along with the develop…
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Classification is a Strong Baseline for Deep Metric Learning Open
Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images. Two major applications of metric learning are content-based image retrieval and face verification. Fo…
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Similarity Learning via Kernel Preserving Embedding Open
Data similarity is a key concept in many data-driven applications. Many algorithms are sensitive to similarity measures. To tackle this fundamental problem, automatically learning of similarity information from data via self-expression has…
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Kinship Verification Using Facial Images by Robust Similarity Learning Open
Kinship verification from face images is a new and challenging problem in pattern recognition and computer vision, and it has many potential real-world applications including social media analysis and children adoptions. Most existing meth…
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Feature-Based Transfer Learning Based on Distribution Similarity Open
Transfer learning has been found helpful at enhancing the target domain's learning process by transferring useful knowledge from other different but related source domains. In many applications, however, collecting and labeling target info…
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Kinship Measurement on Face Images by Structured Similarity Fusion Open
Kinship verification via facial images is an emerging problem in computer vision and biometrics. Recent research has shown that learning a kin similarity measurement plays a critical role in constructing a vision-based kinship measurement …
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Similarity-preserving Image-image Domain Adaptation for Person Re-identification Open
This article studies the domain adaptation problem in person re-identification (re-ID) under a "learning via translation" framework, consisting of two components, 1) translating the labeled images from the source to the target domain in an…
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Recommender System for the Efficient Treatment of COVID-19 Using a Convolutional Neural Network Model and Image Similarity Open
Background: Hospitals face a significant problem meeting patients’ medical needs during epidemics, especially when the number of patients increases rapidly, as seen during the recent COVID-19 pandemic. This study designs a treatment recomm…
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Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid Open
Matching clothing images from customers and online shopping stores has rich applications in E-commerce. Existing algorithms encoded an image as a global feature vector and performed retrieval with the global representation. However, discri…
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Similarity Learning with Higher-Order Graph Convolutions for Brain Network Analysis Open
Learning a similarity metric has gained much attention recently, where the goal is to learn a function that maps input patterns to a target space while preserving the semantic distance in the input space. While most related work focused on…
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Online Multitask Relative Similarity Learning Open
Relative similarity learning~(RSL) aims to learn similarity functions from data with relative constraints. Most previous algorithms developed for RSL are batch-based learning approaches which suffer from poor scalability when dealing with …
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Deep Graph Similarity Learning: A Survey Open
In many domains where data are represented as graphs, learning a similarity metric among graphs is considered a key problem, which can further facilitate various learning tasks, such as classification, clustering, and similarity search. Re…
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Attribute-enhanced metric learning for face retrieval Open
Metric learning is a significant factor for media retrieval. In this paper, we propose an attribute label enhanced metric learning model to assist face image retrieval. Different from general cross-media retrieval, in the proposed model, t…
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Multi-View Cosine Similarity Learning with Application to Face Verification Open
An instance can be easily depicted from different views in pattern recognition, and it is desirable to exploit the information of these views to complement each other. However, most of the metric learning or similarity learning methods are…
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Hierarchical Graph Structure Learning for Multi-View 3D Model Retrieval Open
3D model retrieval has been widely utilized in numerous domains, such as computer-aided design, digital entertainment and virtual reality. Recently, many graph-based methods have been proposed to address this task by using multiple views o…
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Unsupervised Similarity Learning through Cartesian Product of Ranking References for Image Retrieval Tasks Open
Despite the consistent advances in visual features and other Content-Based Image Retrieval techniques, measuring the similarity among images is still a challenging task for effective image retrieval. In this scenario, similarity learning a…