Completer: Incomplete multi-view clustering via contrastive prediction
In this paper, we study two challenging problems in incomplete multi-view clustering
analysis, namely, i) how to learn an informative and consistent representation among …
analysis, namely, i) how to learn an informative and consistent representation among …
Partially view-aligned representation learning with noise-robust contrastive loss
In real-world applications, it is common that only a portion of data is aligned across views
due to spatial, temporal, or spatiotemporal asynchronism, thus leading to the so-called …
due to spatial, temporal, or spatiotemporal asynchronism, thus leading to the so-called …
Hierarchical consensus hashing for cross-modal retrieval
Cross-modal hashing (CMH) has gained much attention due to its effectiveness and
efficiency in facilitating efficient retrieval between different modalities. Whereas, most …
efficiency in facilitating efficient retrieval between different modalities. Whereas, most …
Learning cross-modal retrieval with noisy labels
Recently, cross-modal retrieval is emerging with the help of deep multimodal learning.
However, even for unimodal data, collecting large-scale well-annotated data is expensive …
However, even for unimodal data, collecting large-scale well-annotated data is expensive …
Feature and semantic views consensus hashing for image set classification
Image set classification (ISC) has always been an active topic, primarily due to the fact that
image set can provide more comprehensive information to describe a subject. However, the …
image set can provide more comprehensive information to describe a subject. However, the …
Towards explainable ear recognition systems using deep residual networks
This paper presents ear recognition models constructed with Deep Residual Networks
(ResNet) of various depths. Due to relatively limited amounts of ear images we propose …
(ResNet) of various depths. Due to relatively limited amounts of ear images we propose …
Asymmetric supervised fusion-oriented hashing for cross-modal retrieval
Hashing technologies have been widely applied for large-scale multimodal retrieval tasks
owing to their excellent performance in search and storage tasks. Although some effective …
owing to their excellent performance in search and storage tasks. Although some effective …
Supervised discrete multiple-length hashing for image retrieval
X Nie, X Liu, J Guo, L Wang… - IEEE Transactions on Big …, 2022 - ieeexplore.ieee.org
Hashing can facilitate efficient retrieval and storage for large-scale images due to the binary
representation. In the real applications, the trade-off between retrieval accuracy and speed …
representation. In the real applications, the trade-off between retrieval accuracy and speed …
Prediction of dissolved oxygen content in aquaculture based on clustering and improved ELM
S Cao, L Zhou, Z Zhang - IEEE Access, 2021 - ieeexplore.ieee.org
In the aquaculture industry, dissolved oxygen is an important water quality parameter index.
The prediction of dissolved oxygen can reduce the operation cost of aquatic product …
The prediction of dissolved oxygen can reduce the operation cost of aquatic product …
A clustering-guided contrastive fusion for multi-view representation learning
Multi-view representation learning aims to extract comprehensive information from multiple
sources. It has achieved significant success in applications such as video understanding …
sources. It has achieved significant success in applications such as video understanding …