Learning Protein Embedding to Improve Protein Fold Recognition Using Deep Metric Learning
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00959
Abstract: Protein fold recognition refers to predicting the most likely fold type of the query protein and is a critical step of protein structure and function prediction. With the popularity of deep learning in bioinformatics, protein… read more here.
Keywords: fold recognition; improve protein; protein fold; deep metric ... See more keywords
Rare bioparticle detection via deep metric learning
Sign Up to like & getrecommendations! Published in 2021 at "RSC Advances"
DOI: 10.1039/d1ra02869c
Abstract: Recent deep neural networks have shown superb performance in analyzing bioimages for disease diagnosis and bioparticle classification. Conventional deep neural networks use simple classifiers such as SoftMax to obtain highly accurate results. However, they have… read more here.
Keywords: bioparticle detection; rare bioparticle; rate; detection ... See more keywords
Motor Imagery Classification for Brain Computer Interface Using Deep Metric Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3002459
Abstract: Deep metric learning (DML) has achieved state-of-the-art results in several deep learning applications. However, this type of deep learning models has not been tested on the classification of electrical brain waves (EEG) for brain computer… read more here.
Keywords: metric learning; deep metric; computer interface; classification ... See more keywords
Heterogeneous Double-Head Ensemble for Deep Metric Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3004579
Abstract: The structure of a multi-head ensemble has been employed by many algorithms in various applications including deep metric learning. However, their structures have been empirically designed in a simple way such as using the same… read more here.
Keywords: metric learning; deep metric; structure; head ... See more keywords
A Bayesian Framework for Integrated Deep Metric Learning and Tracking of Vulnerable Road Users Using Automotive Radars
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3077690
Abstract: With the recent advancements in radar systems, radar sensors offer a promising and effective perception of the surrounding. This includes target detection, classification and tracking. Compared to the state-of-the-art, where the state vector of classical… read more here.
Keywords: vulnerable road; metric learning; deep metric; road users ... See more keywords
Probabilistic Principal Geodesic Deep Metric Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3143129
Abstract: Similarity learning which is useful for the purpose of comparing various characteristics of images in the computer vision field has been often applied for deep metric learning (DML). Also, a lot of combinations of pairwise… read more here.
Keywords: metric learning; similarity; principal geodesic; probabilistic principal ... See more keywords
Few-Shot Specific Emitter Identification via Deep Metric Ensemble Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3194967
Abstract: Specific emitter identification (SEI) is a highly potential technology for physical-layer authentication that is one of the most critical supplements for the upper-layer authentication. SEI is based on radio frequency (RF) features from circuit difference,… read more here.
Keywords: identification; emitter identification; identification via; specific emitter ... See more keywords
Toward Tightness of Scalable Neighborhood Component Analysis for Remote-Sensing Image Characterization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3150722
Abstract: Deep metric learning methods have recently drawn significant attention in the field of remote sensing (RS), owing to their prominent capabilities for modeling relations among RS images based on their semantic contents. In the context… read more here.
Keywords: metric learning; image; scalable neighborhood; remote sensing ... See more keywords
Deep Metric Learning for Crowdedness Regression
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2017.2703920
Abstract: Cross-scene regression tasks, such as congestion level detection and crowd counting, are useful but challenging. There are two main problems, which limit the performance of existing algorithms. The first one is that no appropriate congestion-related… read more here.
Keywords: regression; metric learning; learning crowdedness; crowdedness regression ... See more keywords
Visual Explanation for Deep Metric Learning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2021.3107214
Abstract: This work explores the visual explanation for deep metric learning and its applications. As an important problem for learning representation, metric learning has attracted much attention recently, while the interpretation of the metric learning model… read more here.
Keywords: activation; metric learning; deep metric; explanation deep ... See more keywords
Deep Metric Learning With Manifold Class Variability Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2021.3101944
Abstract: In deep metric learning (DML) techniques, understanding both the local and global characteristics of embedding space is essential. However, conventional DML techniques have two limitations as follows: First, Euclidean distance-based metrics never imply global information… read more here.
Keywords: metric learning; space; analysis; deep metric ... See more keywords