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Deep learning is a type of artificial intelligence that enables a security camera to learn various object classifications such as human, animal, vehicle, and so on. Based on these classifications, the camera makes informed decisions about the movement it captures, distinguishing between important activity and insignificant data.
Deep learning prevents false motion detection alarms from being generated by security cameras. As a result, it saves storage space, reduces annoying push notifications, and increases the efficiency of your surveillance system.
The Global Deep learning video camera market accounted for $XX Billion in 2023 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
Uni view’s Prime I 4K vandal dome camera uses deep learning artificial intelligence to recognize pedestrian, motor vehicle, and non-motor vehicle movement. Standard pixel-based motion detection and video analytics are rendered obsolete by this intelligent technology. You solve multiple problems at once by focusing the camera’s attention solely on human agency.
The Vision Cam AI. go includes all of the features needed for the quick and easy implementation of Deep Learning-based image processing solutions. The device is intended to categorize objects into two to five groups.
Users can teach Vision Cam AI. go by simply telling the camera a set of images, with no programming required and supported by an intuitive web GUI. Following that, the intelligent AI camera learns new images entirely on its own. This requires no GPU computers, nor is sensitive data sent to the cloud. The system is ready to use as a fully functional inspection system in minutes. Only the user’s imagination limits the application possibilities.
AWS Deep Lens literally puts machine learning in the hands of developers, with a fully programmable video camera, tutorials, code, and pre-trained models designed to expand deep learning skills.
The AWS Deep Lens (2019 Edition) has improved hardware and software to make the device even easier to set up, allowing you to get started with machine learning faster.
Use Neuro technology to deploy your trained neural network to the FLIR Firefly DL and reduce system cost and complexity by making decisions on-camera without a host PC.
The Firefly DL camera is ideal for embedding into mobile, desktop, and handheld systems due to its small size, low weight, and low power consumption.
