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Blazars and in particular the subclass of high synchrotron peaked ActiveGalactic Nuclei are among the main targets for the present generation ofImaging Atmospheric Cherenkov Telescopes (IACTs) and will remain of greatimportance for very high-energy $\gamma$-ray science in the era of theCherenkov Telescope Array (CTA). Observations by IACTs, which have relativelysmall fields of view ($\sim$ few degrees), are limited by viewing conditions;therefore, it is important to select the most promising targets in order toincrease the number of detections. The aim of this paper is to search forunclassified blazars among known $\gamma$-ray sources from the Fermi Large AreaTelescope (LAT) third source catalog that are likely detectable with IACTs orCTA. We use an artificial neural network algorithm and updated analysis ofFermi-LAT data. We found 80 $\gamma$-ray source candidates, and for thehighest-confidence candidates, we calculate their potential detectability withIACTs and CTA based on an extrapolation of their energy spectra. Follow-upobservations of our source candidates could significantly increase the currentTeV source population sample and could ultimately confirm the efficiency of ouralgorithm to select TeV sources.

Identifying TeV Source Candidates among Fermi-LAT Unclassified Blazars