Results 31 to 40 of about 762,608 (309)
Few-Shot Image Classification via Mutual Distillation
Applied Sciences, 2023 Due to their compelling performance and appealing simplicity, metric-based meta-learning approaches are gaining increasing attention for addressing the challenges of few-shot image classification.
Tianshu Zhang +5 more
doaj +1 more source
Distribution probability‐based self‐adaption metric learning for person re‐identification
IET Computer Vision, 2022 Person re‐identification addresses the problem of pedestrian image matching in a non‐overlapped surveillance network. Traditional metric learning methods try to learn a fixed pedestrian images matching metric model.
Yutao Ren, Zhangcan Huang
doaj +1 more source
A Multi-Layer Feature Fusion Method for Few-Shot Image Classification
Sensors, 2023 In image classification, few-shot learning deals with recognizing visual categories from a few tagged examples. The degree of expressiveness of the encoded features in this scenario is a crucial question that needs to be addressed in the models being ...
Jacó C. Gomes +2 more
doaj +1 more source
Journal of Machine Learning Research, 2011 Transportation distances have been used for more than a decade now in machine learning to compare histograms of features. They have one parameter: the ground metric, which can be any metric between the features themselves. As is the case for all parameterized distances, transportation distances can only prove useful in practice when this parameter is ...
CuturiMarco, AvisDavid
openaire +3 more sources
Deep metric learning to rank [PDF]
, 2019 We propose a novel deep metric learning method by revisiting the learning to rank approach. Our method, named FastAP, optimizes the rank-based Average Precision measure, using an approximation derived from distance quantization.
Cakir, Fatih +4 more
core +1 more source
Distributed Semi-Supervised Metric Learning
IEEE Access, 2016 Over the last decade, many pairwise-constraint-based metric learning algorithms have been developed to automatically learn application-specific metrics from data under similarity/dissimilarity data-pair constraints (weak labels).
Pengcheng Shen, Xin Du, Chunguang Li
doaj +1 more source
Collaborative Translational Metric Learning [PDF]
2018 IEEE International Conference on Data Mining (ICDM), 2018 ICDM 2018 Full ...
Xing Xie +3 more
openaire +3 more sources
Multi-View Cosine Similarity Learning with Application to Face Verification
Mathematics, 2022 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.
Zining Wang, Jiawei Chen, Junlin Hu
doaj +1 more source
Learning Sequence Neighbourhood Metrics [PDF]
, 2012 Recurrent neural networks (RNNs) in combination with a pooling operator and the neighbourhood components analysis (NCA) objective function are able to detect the characterizing dynamics of sequences and embed them into a fixed-length vector space of arbitrary dimensionality.
Bayer, Justin +2 more
openaire +4 more sources
Agriculture, 2023 As machine vision technology has advanced, pig face recognition has gained wide attention as an individual pig identification method. This study establishes an improved ResNAM network as a backbone network for pig face image feature extraction by ...
Rong Wang +3 more
doaj +1 more source