The phrase "data modalities" is grammatically correct and can be used in written English.
It refers to the various forms or modes in which data can be presented or collected. Example: The researchers analyzed the study data using different modalities, such as surveys, interviews, and observations.
In fact, other interesting data modalities that we could consider would be infrared images, photo-sketch based images etc. Figure 4 Categorization of landmarking approaches.
Even though clusters typically form around nodes with tight edges and similar attributes, existing methods have only focused on one of these two data modalities.
A wide range of mathematical approaches have been proposed for addressing this challenge, often targeted towards specific data modalities, species or recording environments.
This chapter is a review of the data and informatics resources available to the public, as well as a discourse on the power of integrating data modalities to understand and discover fundamental brain properties.
To capture more general forms of association and allow the number of topics in the two data modalities to be different, topic regression multimodal latent Dirichlet allocation (tr-mmLDA) [30] was proposed by introducing a regression module to correlate the two sets of topics.
Success in these tasks often requires the integration of various sensor or data modalities such as video, audio, motion, and accompanying text, and typically hinges on a host of machine-learning methodologies to handle the inherent variability and complexity of the ensuing features.
In our combined structured sparse regularization, the group ℓ1-norm regularization (blue circles in Fig. 3) learns the feature global importance, i.e. the modal-wise feature importance of every data modality on each class (task), and the ℓ2,1-norm regularization (red circles in Fig. 3) explores the feature local importance, i.e. the importance of each feature for multiple classes/tasks.
However, we consider 3D as a different data modality rather than a methodological category.
The major landmarking methods in the literature are categorized and reviewed in Section 3. 4 addresses a different data modality: 3D face data.
This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations.
