Metric-based Regularization and Temporal Ensemble for Multi-task Learning using Heterogeneous Unsupervised TasksByung Cheol SongDae Ha KimSeung Hyun Lee
We have proposed a general-purpose, graph-based, multimodal fusion framework that can be used for multimodal data classification. This method is a combination of multimodal metric learning with a graph-based multimodal fusion method. The Bag of Words framework and neural networks have been used for...
Existing deep learning approaches can be divided into three directions: (1) pre-trained deep features [6]; (2) fine-tuned deep features [7]; (3) full-trained deep features [8], [9]. Actually, for practical scene recognition tasks, it is hard to fully train a new deep CNN model ...
This metric is valid only for classification tasks. example metric = accuracyMetric(PropertyName=Value) sets the Name, NumTopKClasses (since R2024b), Threshold (since R2025a), NetworkOutput, AverageType, and ClassificationMode properties using name-value arguments. Properties expand all Name— Metri...
This repository is dedicated for my term paper after the 3rd year on the topic "Triplet loss modifications for deep metric learning tasks". All code of experiments can be found here. This code uses Python language, PyTorch and Open Metric Learning libraries with all their dependecies. All requ...
Ensemble Learning: Ensemble learning combines the outcomes of several weak learners for the final predic- tion, which has been proven to be effective in a vari- ety of machine learning tasks such as supervised learn- ing [36, 39, 39], reinforcement learning [4, 30, 62], and unsupervised ...
CVSRN introduces two key innovations for SEI: the Complex-Valued Separate Residual (CVSpeRes) module, which uses complex-valued convolutions to better capture the interaction between real and imaginary components of I/Q signals, and a multiscale learning architecture that improves feature extraction ...
The classification of these images is a relevant aid for physicians who have to process a large number of images in long and repetitive tasks. This work proposes the adoption of metric learning that, beyond the task of classifying images, can provide additional information able to support the ...
Microsoft.StorageTasks儲存任務 N/A Microsoft.VoiceServicesCommunicationsGateways N/A Private.MessagingConnectors私人訊息連接器/連接器 N/A Wandisco.FusionWandisco.Fusion/遷移者 Wandisco.Fusion/migrators/dataTransferAgents Wandisco.Fusion/migrators/liveDataMigrations ...
Note that Npairs∗ applies the multi-scale test while all other methods take a single crop test. For SemiHard [21], we report the result recorded in [23]. First, it is surprising to observe that the performance of SoftMaxnorm surpasses that of the existing ...