Learning Single‐Cell Distances from Cytometry Data
Sign Up to like & getrecommendations! Published in 2019 at "Cytometry Part A"
DOI: 10.1002/cyto.a.23792
Abstract: Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric,… read more here.
Keywords: single cell; cell; distance metric; cytometry data ... See more keywords
Person re-identification based on metric learning: a survey
Sign Up to like & getrecommendations! Published in 2021 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-10953-6
Abstract: Person re-identification is a challenging research issue in computer vision and has a broad application prospect in intelligent security. In recent years, with the emergence of large-scale person datasets and the rapid development of deep… read more here.
Keywords: distance metric; person; person identification; metric learning ... See more keywords
Bayesian distance metric learning for discriminative fuzzy c-means clustering
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.08.071
Abstract: Abstract A great number of machine learning algorithms strongly depend on the underlying distance metric for representing the important correlations of input data. Distance metric learning is defined as learning an appropriate similarity or distance… read more here.
Keywords: metric learning; means clustering; distance metric; bayesian distance ... See more keywords
A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.08.017
Abstract: Abstract Distance metric learning is a branch of machine learning that aims to learn distances from the data, which enhances the performance of similarity-based algorithms. This tutorial provides a theoretical background and foundations on this… read more here.
Keywords: distance metric; mathematical foundations; metric learning; experimental analysis ... See more keywords
How to Find a Perfect Data Scientist: A Distance-Metric Learning Approach
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2870535
Abstract: The title of data scientist has been described as one of the sexiest jobs of the 21st century. Numerous efforts have been made to define the job of a data scientist in a qualitative manner… read more here.
Keywords: data scientist; data scientists; distance metric; scientist ... See more keywords
A Hybrid Model Combining Learning Distance Metric and DAG Support Vector Machine for Multimodal Biometric Recognition
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2020.3035110
Abstract: Metric learning has significantly improved machine learning applications such as face re-identification and image classification using K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) classifiers. However, to the best of our knowledge, it has not… read more here.
Keywords: biometric recognition; distance metric; multimodal biometric;
Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Biomedical Engineering"
DOI: 10.1109/tbme.2017.2688453
Abstract: While the accurate delineation of tumor volumes in FDG-positron emission tomography (PET) is a vital task for diverse objectives in clinical oncology, noise and blur due to the imaging system make it a challenging work.… read more here.
Keywords: pet; evidential clustering; pet images; tumor segmentation ... See more keywords
Predicting Cancer Lymph-node Metastasis from LncRNA Expression Profiles using Local Linear Reconstruction Guided Distance Metric Learning.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2022.3149791
Abstract: Lymph-node metastasis is the most perilous cancer progressive state, where long non-coding RNA (lncRNA) has been confirmed to be an important genetic indicator in cancer prediction. However, lncRNA expression profile is often characterized of large… read more here.
Keywords: lymph node; node metastasis; distance metric; cancer ... See more keywords
Robust Distance Metric Learning via Bayesian Inference
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2017.2782366
Abstract: Distance metric learning (DML) has achieved great success in many computer vision tasks. However, most existing DML algorithms are based on point estimation, and thus are sensitive to the choice of training examples and tend… read more here.
Keywords: bayesian inference; label noise; metric learning; distance metric ... See more keywords
Point-to-Set Distance Metric Learning on Deep Representations for Visual Tracking
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2017.2766093
Abstract: For autonomous driving application, a car shall be able to track objects in the scene in order to estimate where and how they will move such that the tracker embedded in the car can efficiently… read more here.
Keywords: distance metric; point set; target; metric learning ... See more keywords
Deep Discriminative Feature Models (DDFMs) for Set Based Face Recognition and Distance Metric Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3205939
Abstract: This article introduces two methods that find compact deep feature models for approximating images in set based face recognition problems. The proposed method treats each image set as a nonlinear face manifold that is composed… read more here.
Keywords: distance metric; face recognition; feature; metric learning ... See more keywords