Ranking-based triplet loss function with intra-class mean and variance for fine-grained classification tasks
Sign Up to like & getrecommendations! Published in 2020 at "Soft Computing"
DOI: 10.1007/s00500-020-04880-1
Abstract: This paper proposed a deep ranking model for triplet selection to efficiently learn similarity metric from top ranked images. A modified distance criterion described in the current work leverages the intra-category variance in metric learning… read more here.
Keywords: triplet; fine grained; loss function; variance ... See more keywords
Automated assessment of Parkinsonian finger-tapping tests through a vision-based fine-grained classification model
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.02.011
Abstract: Abstract Movement disorder of Parkinson’s disease (PD) is usually quantified by the Movement Disorders Society-sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) to evaluate its severity. However, the lack of well-trained experts and… read more here.
Keywords: automated assessment; model; fine grained; finger tapping ... See more keywords
Dual-Polarized SAR Ship Grained Classification Based on CNN With Hybrid Channel Feature Loss
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3067678
Abstract: This letter proposes a novel convolutional neural network (CNN) method for dual-polarized synthetic aperture radar (SAR) ship grained classification. The network employs hybrid channel feature loss that jointly utilizes the information contained in the polarized… read more here.
Keywords: dual polarized; loss; ship grained; sar ship ... See more keywords
EFM-Net: An Essential Feature Mining Network for Target Fine-Grained Classification in Optical Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3265669
Abstract: Target fine-grained classification has been the research hotspot in remote sensing image interpretation, which has received general attention in application fields. One challenge of the fine-grained classification task is to learn the most discriminative feature… read more here.
Keywords: grained classification; remote sensing; essential feature; feature ... See more keywords
Bilinear CNN Model for Fine-Grained Classification Based on Subcategory-Similarity Measurement
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DOI: 10.3390/app9020301
Abstract: One of the challenges in fine-grained classification is that subcategories with significant similarity are hard to be distinguished due to the equal treatment of all subcategories in existing algorithms. In order to solve this problem,… read more here.
Keywords: similarity; measurement; fine grained; classification ... See more keywords