sparse codingprobabilistic latent semantic analysisBUAA-SID 1.0Traditional satellite recognition usually applies low-level features (e.g., invariant moment) to describe the global information of satellites. Therefore, the local property and the latent high-level semantic concepts of satellites are likely ...
Standard techniques {e.g., latent semantic analysis (LSA) [33,113,114] and word2vec [34]} generate embeddings with uninterpretable dimensions, but, when embeddings are constrained to be both sparse (zeros on most dimensions) and non-negative (only positive values on the rest), the ...
I’ll explain what it is, why it matters, and how to execute a successful semantic SEO strategy. Hint: It’s all about using semantic keywords, sometimes previously called latent semantic indexing (LSI) keywords.
Cross-modal retrieval has become a topic of popularity, since multi-data is heterogeneous and the similarities between different forms of information are worthy of attention. Traditional single-modal methods reconstruct the original information and lack of considering the semantic similarity between differen...
These methods are subjective and easily creates inconsistencies. In order to have an objective and statistical relationships map, we propose a Latent Semantic Analysis (LSA) based modal to generate a specific relatedness correlation map. We created a relatedness map of a banking regulation to a ...
At present, the two most common measurement methods are maximizing correlation and minimizing Euclidean distance25. The typical methods to maximize correlation are CCA23 and improved methods, learning a latent space that maximizes the correlation between the projection features of the two ...
To tackle this problem, many retrieval methods based on machine learning techniques have been proposed, such as caption generation [21, 24, 38] or the mapping of features into a common latent space between text and images [9, 25]. However, such methods still cannot deal with spatial ...
SN Computer Science (2021) 2:443 https://doi.org/10.1007/s42979-021-00832-0 ORIGINAL RESEARCH Expertise Detection in Crowdsourcing Forums Using the Composition of Latent Topics and Joint Syntactic–Semantic Cues Yonas Demeke Woldemariam1 Received: 23 February 2021 / Accepted: 23...
Fig. 1. Examples of three images and their object lists from the SUN database. 2. Method 2.1. Processing of the scene dataset We used latent semantic analysis (LSA; Landauer & Dumais, 1997) to investigate patterns in visual object co-occurrence. LSA is a well-known technique for constructi...
He, K., et al., “Momentum contrast for unsupervised visual representation learning,” In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9729-9738, 2020. Grill, J.B., et al., “Bootstrap your own latent: A new approach to self-supervised learning,” Neural Info...