Sentence examples for model for detection from inspiring English sources

This is a perfectly correct and usable phrase in written English.
You can use it to refer to a system, process, or technique which is used for the act of recognizing and/or identifying something. For example: The researchers developed a sophisticated model for detection of early-stage breast cancer.

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There is no model for detection.

Thus, with limited training data, MTANNs would be a suitable end-to-end machine-learning model for detection and classification of focal lesions that do not require high-level semantic features.

The watch runs a distinct model for detection that isn't as large as the full neural network running on the iPhone or as small as the initial detector.

Leemput et al. [58] designed an automated method by using an intensity-based tissue classification and a stochastic model for detection of MS lesions from 3-D images.

Open image in new window Fig. 7 Color filter a road region result from road map layer, b corresponding road regions in terrain layer (annotated by light-pink) to learn color model for detection, c road candidate regions (annotated by light-pink) using color detection.

We can summarize our design problem as "Given the CSI, REI, and QoI for each sensor, how can we find the optimal transmission control policy (XCP) for each sensor that maximizes the system detection performance?" Figure 1 System model for detection in one-hop sensor networks.

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In this thesis, I present two instantiations of model parsimony for large scale object detection and discovery.

The time-dependent model for detection-rate changes combined with b-value changes defined in Model and Methods section was applied to all of the compiled events with magnitudes given in the Hypocenter Catalog of the JMA for the 5-day period after the M6.5 event.

Moreover, geophysical modeling for detection of deep structures is included in the GEMex project.

Linda et al. [44] presented an IDS using NN-based modeling for detection of anomalous activities.

This method overcomes some limitations of logistic regression modeling for detection and characterization of gene-gene interactions.

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