In recent times, the healthcare industry has faced many challenges due to lesser resources. But the usage of smart sensors with AI-enabled microphones and cameras has a lot of benefits. Such a device ensures public safety, improves patient care, and enhances operational efficiency in the industry.
Advanced computer vision technology has made it possible to detect a rise in human temperature. This helps identify people infected with the Coronavirus. Many organizations use thermometers for this purpose, but it is a labor-intensive method that generates a queue of people. This creates a bottleneck at entry and exit points and increases risks due to human contacts.
Deep Vision AI and Intelisite have combined the advanced computer vision technology of Deep Vision with the all-in-one human-based monitoring system of intellisite. Together, they make a smart application which can detect people with an increased temperature, thus identifying individuals at high risk. This application also enables an alert for prompt tracking of data.
Deep Vision AI uses NVIDIA GPU
DeepVision specializes in analyzing visual content and fetching values out of the data using Visual recognition technology. It permits enterprises to organize images, perform analysis, fetch insights, and recommend solutions.
Here are some uses of DeepVision AI:
- Face, Brand, and Context Analysis: Visual Intelligence API is helpful for industries, such as e-commerce and online options, retailers, and media entertainment. It helps in the analysis of content related to faces, brands, and contexts.
- Vehicle recognition: The vehicle recognition model of Deep Vision AI can easily fetch someone the year, make, license, and model plates of the vehicles. This model is being used by the Government to analyze the flow of vehicles and send warnings for designated vehicles breaking the law. This model can also fetch demographic information using vehicle recognition. Other than that, it helps identify changing traffic patterns and flow of vehicles.
The vehicle recognition model is also used by advertisers for generating contextualized ads related to changing demographics and understanding the ROI for outdoor advertising.
- People counting across age and gender: The demographics software module of Deep Vision AI regularly monitors different target zones to get the gender, count, age, and other identification of individuals over time. This way, it aids in understanding the demographic variations occurring over time in a designated area in a city, tracking customer patterns in retail stores, and more.
Advertisers and brands can use this model to target specific groups of people for advertising and placement of products.
- Facial recognition: The facial recognition model uses the recognition software that monitors target zones, tracks unique individuals, and provides facial matches for the specified ones. Overall, this model helps improve security and safety. This is ensured by extracting the maximum value as compared to the traditional security measures, helping retailers in recognizing the essential customers, or evaluating the frequency of the visitors.
Some benefits of Deep Vision AI include:
- Auto detection of objects: DeepVision AI helps detect and classify different objects present in an image. It also helps identify their locations. This helps the user easily and conveniently receive information.
- Reduce purchase friction: The Vision Products search API of Deep Vision AI can help retailers create a great mobile experience. This can be done by enabling customers to upload a photo of the product, following which, they would be able to get a list of similar items.
Two key features used by the Vision AI are as below:
- Auto ML Vision: It helps the training of Machine Learning models. For this, one needs to upload images and then train the custom image model using the auto ML Vision feature. It has an easy to use graphical interface that further helps in the optimization of the model for latency, accuracy, and size. Also, the feature helps in the export of the model to the respective application present in the cloud or an array of devices.
- Vision API: Vision API is another powerful feature used for the pre-training of Machine Learning models via RPC and REST APIs. It adds labels to the images and classifies them quickly into predefined categories. It detects faces and objects, reads handwritten or printed texts, and builds MetaData in the image catalog.
To sum up, Deep Vision AI - using the NVIDIA GPU Cloud - has revolutionized various industries. It helps in the detection of objects in images and classification of images, offering a number of use cases as discussed above.
You can also get the cloud GPUs deployed for your organization. This can accelerate some of your high-performing applications. The GPU cloud by E2E supports almost all deep learning frameworks.
Contact E2E Cloud for all your cloud GPU needs.