Suchergebnisse - "Semi-supervised autoencoder"

Improved semi-supervised autoencoder for deception detection von Fu, Hongliang, Lei, Peizhi, Tao, Huawei, Zhao, Li, Yang, Jing

“… This model updates and optimizes the semi-supervised autoencoder and it consists of two layers of encoder and decoder, and a classifier …”
Volltext

A semi-supervised autoencoder for autism disease diagnosis von Yin, Wutao, Li, Longhai, Wu, Fang-Xiang

“… In this paper, we proposed a semi-supervised autoencoder (AE) for autism diagnosis using functional connectivity (FC …”
Volltext

Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum von Jang, Hee-Deok, Kwon, Seokjoon, Nam, Hyunwoo, Chang, Dong Eui

“… In this paper, we propose a deep neural network utilizing a semi-supervised autoencoder (SSAE) for the classification of chemical gases based on FTIR spectra …”
Volltext

A Semi-Supervised Autoencoder-Based Approach for Protein Function Prediction von Dhanuka, Richa, Tripathi, Anushree, Singh, Jyoti P.

“… After the development of next-generation sequencing techniques, protein sequences are abundantly available. Determining the functional characteristics of these …”
Volltext

scSSA: A clustering method for single cell RNA-seq data based on semi-supervised autoencoder von Zhao, Jian-Ping, Hou, Tong-Shuai, Su, Yansen, Zheng, Chun-Hou

“… •In this study, We proposed to use semi-supervised autoencoder to reduce the dimension of data, because it makes good use of some existing label information …”
Volltext

Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace von Zhou, Ping, Zhao, Peng, Ou, Zihui, Chai, Tianyou

“… This paper proposes a novel stacked semi-supervised autoencoder-regularized random vector functional-link networks (RVFLNs …”
Volltext

A semi-supervised autoencoder framework for joint generation and classification of breathing von Pastor-Serrano, Oscar, Lathouwers, Danny, Perkó, Zoltán

“… •Models of breathing motion using 1D convolutional neural networks and probabilistic autoencoders.•A novel semi-supervised algorithm based on Adversarial …”
Volltext

A Semi-Supervised Autoencoder With an Auxiliary Task (SAAT) for Power Transformer Fault Diagnosis Using Dissolved Gas Analysis von Kim, Sunuwe, Jo, Soo-Ho, Kim, Wongon, Park, Jongmin, Jeong, Jingyo, Han, Yeongmin, Kim, Daeil, Youn, Byeng Dong

“… This paper proposes a semi-supervised autoencoder with an auxiliary task (SAAT) to extract a health feature space for power transformer fault diagnosis using dissolved gas analysis (DGA …”
Volltext

Discriminant autoencoder for feature extraction in fault diagnosis von Luo, Xiaoyi, Li, Xianmin, Wang, Ziyang, Liang, Jun

“… when handling ultimate discriminative task. In this paper, we propose a novel semi-supervised autoencoder, which is named as Discriminant Autoencoder …”
Volltext

Representation Learning via Semi-Supervised Autoencoder for Multi-task Learning von Zhuang, Fuzhen, Luo, Dan, Jin, Xin, Xiong, Hui, Luo, Ping, He, Qing

“… Multi-task learning aims at learning multiple related but different tasks. In general, there are two ways for multi-task learning. One is to exploit the small …”
Volltext

Ironmaking process modeling uncertainty quantification via conformal prediction based on random vector functional link networks von Zhou, Ping, Wen, Chaoyao, Zhao, Peng, Li, Mingjie

“… Firstly, to address the issue that shallow learning models have limited expression capabilities to describe complex nonlinear relationships, the dynamic attention mechanism and semi-supervised …”
Volltext

AutoFuse: A Semi-supervised Autoencoder based Multi-Sensor Fusion Framework von Kumar, Kriti, Sahu, Saurabh, Majumdar, Angshul, Chandra, M Girish

“… The performance of existing methods for multisensor fusion are severely affected by the lack of significant amount of labeled data. In most practical …”
Volltext

Tree Health Assessment from UAV Images: Improving Object Detection and Classification Using Hard Negative Mining and Semi-Supervised Autoencoder von Jemaa, Hela, Bouachir, Wassim, Leblon, Brigitte, LaRocque, Armand, Haddadi, Ata, Bouguila, Nizar

“… Orchard tree inventory has been an essential step to obtain up-to-date information for effective tree treatments and crop insurance purposes. Inventorying …”
Volltext

Semi-Supervised Autoencoder: A Joint Approach of Representation and Classification von Haiyan, Wu, Haomin, Yang, Xueming, Li, Haijun, Ren

“… Recent years have witnessed the significant success of representation learning and deep learning in various prediction and recognition applications. Most of …”
Volltext

A semi-supervised autoencoder framework for joint generation and classification of breathing von Pastor-Serrano, Oscar, Lathouwers, Danny, Perkó, Zoltán

“… One of the main problems with biomedical signals is the limited amount of patient-specific data and the significant amount of time needed to record the …”
Volltext

Mental workload recognition from EEG signals via semi-supervised autoencoders von Liu, Qi, Jiang, Xu, Wang, Huanjie, Chen, Jingjing

“… To address this, we propose semi-supervised autoencoders that combine labeled and abundant unlabeled data …”
Volltext

Explaining anomalies through semi-supervised Autoencoders von Angiulli, Fabrizio, Fassetti, Fabio, Ferragina, Luca, Nisticò, Simona

“… This work tackles the problem of designing explainable by design anomaly detectors, which provide intelligible explanations to abnormal behaviors in input data …”
Volltext

Context-aware ranking refinement with attentive semi-supervised autoencoders von Xu, Bo, Lin, Hongfei, Lin, Yuan, Xu, Kan

“… Based on the top-ranked feedback documents, we propose an attentive semi-supervised autoencoder to refine the ranked results using an optimized ranking-oriented reconstruction loss …”
Volltext

AdImpute: An Imputation Method for Single-Cell RNA-Seq Data Based on Semi-Supervised Autoencoders von Xu, Li, Xu, Yin, Xue, Tong, Zhang, Xinyu, Li, Jin

“… This paper presents AdImpute: an imputation method based on semi-supervised autoencoders. The method uses another imputation method …”
Volltext

Energy Reconstruction with Semi-Supervised Autoencoders for Dual-Phase Time Projection Chambers von Li, Ivy, Higuera, Aarón, Liang, Shixiao, Qin, Juehang, Tunnell, Christopher

“… This paper presents a proof-of-concept semi-supervised autoencoder for the energy reconstruction of scattering particle interactions inside dualphase time projection chambers (TPCs), such as XENONnT …”
Volltext