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Fully featured bullet camera with deep learning for all-around coverage in 2 MP

2 minutes read
AXIS P14 Series

Axis Communications announces a new bullet camera featuring a deep learning processing unit (DLPU) to enable intelligent applications based on deep learning on the edge. Built on the latest Axis system-on-chip, it comes pre-installed with AXIS Object Analytics offering detection and classification of humans, vehicles, and types of vehicles—all tailored to specific needs.

Part of the recently updated AXIS P14 Series, AXIS P1465-LE delivers excellent image quality with forensic details in 2 MP at up to 60 fps. This series now offers a range of ARTPEC-8 bullet cameras from 2 MP to 4K resolution including AXIS P1467-LE and P1468-LE. In addition, the series includes AXIS P1455-LE offering HDTV 1080p resolution at up to 60 fps.

Ideal for various surveillance scenarios, this bullet camera features Lightfinder 2.0, Forensic WDR, and OptimizedIR to deliver true colors and great detail under any light conditions. With edge-to-edge technology, it can be connected to an Axis network speaker enabling two-way audio. Additionally, it’s available in two variants with a choice of lenses: a wide 9 mm lens for wide area surveillance and a tele 29 mm lens for surveillance from a distance.

Key features include:

  • Lightfinder 2.0, Forensic WDR, OptimizedIR
  • Analytics with deep learning
  • Audio and I/O connectivity
  • Built-in cybersecurity features
  • Impact and weather resistant

This robust, outdoor-ready camera can withstand winds up to 50 m/s. With IP66/67, NEMA 4X, and IK10 ratings, it’s protected from dust, rain, snow, and impacts. Furthermore, it offers built-in cybersecurity features to help prevent unauthorized access and safeguard your system. For instance, Axis Edge Vault protects the Axis device ID and simplifies authorization of Axis products on the network.

Learn more about
Madeleine Eibrand
Press contact
Communications Manager, Brand & Thought Leadership, Axis Communications
Phone: +46 46 272 18 00
Madeleine Eibrand
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