Semi-supervised clusteringWeighted consensusEnsemble learningPairwise similaritiesRobust clusteringWith the growing prevalence of unstructured and noisy data in real-world applications, developing noise-robust semi-supervised clustering methods has become increasingly critical. Existing approaches often face ...
Despite the recent developments in the field of cross-modal retrieval, there has been less research focusing on low-resource languages due to the lack of manually annotated datasets. In this paper, we propose a noise-robust cross-lingual cross-modal retrieval method for low-resource languages. ...
https://github.com/noise-learning/SelfMix/blob/maingithub.com/noise-learning/SelfMix/blob/main 一、概述 在工业界的很多实际任务中,都难免会遇到数据中存在噪音的情况。虽然这几年大型预训练模型的出现,让噪音数据的影响没那么大了。但是噪音样本比例大于一定情况的时候,大模型也会受到影响。目前解决噪音样...
master 1Branch0Tags Code This branch is15 commits ahead of,2 commits behindLiJiaBei-7/nrccr:master. README License Cross-Lingual Cross-Modal Retrieval with Noise-Robust Learning source code of our paperCross-Lingual Cross-Modal Retrieval with Noise-Robust Learning ...
本文提出了一个基于参数分类的鲁棒噪声学习方法。本文通过神经网络先拟合clean data,后记忆noisy data的特性,结合彩票假设(lottery ticket hypothesis),将参数划分为核心参数(critical parameter)与非核心参数(non-critical parameter),采用不同的更新规则,使得模型在学习clean data的同时,阻碍noisy data的记忆,达到鲁棒噪声...
The learning variables of the dynamic filter are jointly optimized with KWS weights by using Cross-Entropy (CE) loss. CE loss alone, however, is not sufficient for high performance when the SNR is low. In order to train the network for more robust performance in noisy environments, we ...
In recent years, radar automatic target recognition (RATR) utilizing high-resolution range profiles (HRRPs) has received significant attention. Approaches based on deep learning have demonstrated remarkable efficacy in HRRP recognition tasks. However, th
In recent years, 3D human pose estimation has seen significant advancements with improvements in deep learning techniques and computational resources. This section reviews the various approaches for 3D human pose estimation and edge AI approaches. 2.1. 3D Human Pose Estimation In the rapid development ...
A challenging, unsolved problem in the speech recognition community is recognizing speech signals that are corrupted by loud, highly nonstationary noise. One approach to noisy speech recognition is to automatically remove the noise from the cepstrum sequence before feeding...
Partially View-aligned Representation Learning with Noise-robust Contrastive Loss Requirements pytorch==1.5.0 numpy>=1.18.2 scikit-learn>=0.22.2 munkres>=1.1.2 logging>=0.5.1.2 Configuration The hyper-parameters, the training options (including the ratiao of positive to negative, aligned proportions...