In recent years, multi-view clustering algorithms have shown promising performance by combining multiple sources or views of datasets. A problem that has not been addressed satisfactorily is the uncertain relationship between an object and a cluster. Thus, this paper investigates an active three-way ...
In recent years, deep learning (DL)-based approaches have shown initial success in annotating enzyme active sites. For example, Gligorijević et al.18proposed a graph convolutional neural network for protein function prediction based on structures. Although it was not explicitly trained on active ...
[51] study human activity recognition and propose a deep and active learning enabled model (DeActive) that adopts a simple k-means clustering AL approach. DeActive clusters features and selects the most informative samples according to a density-weighted heuristic. Samples found within the most ...
Egocentric Deep Multi-Channel Audio-Visual Active Speaker Localization Hao Jiang, Calvin Murdock, Vamsi Krishna Ithapu Reality Labs Research at Meta {haojiang,cmurdock,ithapu}@fb.com Abstract Augmented reality devices have the potential to enhance human perception and ...
We trained a Multi-layer Perceptron (MLP) classifier using the annotated representatives’ cells and used it to predict the cell types of the rest of the non-representative samples’ cells generated by the deep learning model. As shown in Fig. 2b, cell clustering remains intact in the semi-...
Firstly, the contour of the nodule area in the ultrasound image was approximated by the spatial NLM (SNLM) clustering method with spatial information. Subsequently, the SNLM was used to initialize and regularize the level set by estimating the parameters in the evolving equation. SNDRLS model ...
At the drug level, the predictions of the model correlated strongly amongst drugs of similar mechanisms. Hierarchical clustering of predictions (Supplementary Fig.4d) grouped targeted therapies (top left) distinctly from more broad-spectrum cytotoxic agents (bottom right). Among the targeted therapies,...
Another way to perform online active learning in time-varying data streams is to use clustering-based approaches. Halder et al. (2023) extended the framework based on stable and dynamic classifiers by introducing a clustering step that aims to train the new stable classifier \(C_s\) on the ...
Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation Nat. Cell Biol., 26 (2024), pp. 153-167, 10.1038/s41556-023-01316-4 View in ScopusGoogle Scholar 33 R. Movva, P. Greenside, G.K. Marinov, S. Nair, A. Shrikumar, A...
This paper presents a deep learning model based on an active learning strategy. The model achieves accurate identification of vegetation types in the study area by utilizing multispectral data obtained from preprocessing of unmanned aerial vehicle (UAV) remote sensing equipment. This approach offers adva...