The use of computer vision and its applications is vast and currently realising potential. This is simply because, vision is the best sensory function out of the 5 sense organs that a human being comprehends well in gathering intelligence. By far, 80% of all the impressions perceived are through vision. And if other senses such as taste or smell stop working, it’s the vision that best protect us from danger.
Considering this possibility, we welcome you to untapping the immense value offered by Computer Vision through Artificial Intelligence. The permutation combinations are vast for this technology where it finds application. A few of the use cases are mentioned below, notwithstanding to the few.
Different industries and scenarios demand different solutions. Depending on the industry we design the solution considering various factors like public or private entity, permissible levels, scalability levels, complexity of contract among peers etc.
No matter where you are in your implementation journey we offer comprehensive suite of services to add new values and gain competive advantage.
ACQUIRING THE IMAGE
With the availability of large and advance set of sensor and Iot, the techniques for image acquisition are at a continuous improvement stage. This would be either using a camera or sensor packed camera system to capture the image as desirous for the system.
ANALYZING THE IMAGE
For e.g., while capturing an image, there are so many details an image can say. An analysis would mean creating boundaries on the image landscape which would set a foundation to apply the insights.
APPLYING THE INSIGHTS
With hours of training imparted to the neural network models using training data, the analyzed images are fed into CNN’s such that the requisite insights are delivered based on what the system is designed for.
There are many scenarios for which we have a distance measuring tool. One example, basis the current scenario would be to understand or gauge social distancing. Computer vision technology can play a vital role by tracking people in an area or a particular perimeter to know whether social distancing norms are being followed or not.
The application can be developed for object detection and tracking in real-time. For eg:, The solution logic could be, to detect each person present in a frame using a bounding box or imaginary square that serves as a point of reference for object detection. Then track the movement of each box in the frame and calculate the distance between all the boxes. If there is a violation being detected then those bounding boxes can be highlighted.
HPE is a computer vision technology to identify the posture of a person or object present in the image frame. A tool created to perform this activity identifies the set of coordinates to define the pose of a person. This could be done in many ways. One way is to identify limbs. A pair of coordinates is identified as limb. Further, pose estimation is performed by identifying, locating, and tracking the key points of humans pose in an Image or in a video. Areas where currently the solution is predominant are augmented reality experience, surveillance systems, robotics, animation etc
MDA is a specialised field in the safety and security of the global maritime domain. This would include illegal fishing, drug enforcement, invading marine sanctuaries etc. With computer vision using AI in place, the machine learning algorithms are trained using sensor data to alert the end user for detecting such anomalies occurring in this space. The applications would include
Right environment ensures success in agriculture. While we mean the right environment, it would cater to a multitude of factors which would include weather forecasts, soil conditions, seed quality, impact of weeds, pests, specific amount of plant nutrition provided etc.
All the above factors can be deduced to a data model using data collected from sensors and used for monitoring the agriculture such that any anomaly will be soon detected and alerted. This goes well within predictive models also, based on which a farmer can estimate how the best methods can be employed to get the best harvest based on the intelligence provided by predictive models. With this technology available farming is becoming more precise, quality of produce is ensured, a huge savings on decreased crop fallout is achieved.
Here is where computer vision is bringing drastic changes to farming where sensors are able to identify major diseases that can occur to fruits and alert the farmer through the abnormal changes in ripening time. The technology is also capable while using Indoor farming where the conditions are artificially set for farming and all the data can be fed to model which constantly monitors the parameters be it weed detection, pest attack etc. One major advantage of AI is it can be deployed in scale, where a drone can pan the entire area within minutes to check on the farms based on the trained data models.
CNNs and modern machine learning scale to learn from billions of examples resulting in an extraordinary capacity to learn highly complex behaviors and thousands of categories. Thanks to high volumes of data and powerful computing resources, FIQ intelligence technology can train powerful and highly accurate models.
Our trained models store their knowledge in a single network, making them easy to deploy in any environment. There is no need to store any additional data when new data is analyzed. This means that the FIQ visual intelligence engine can run on inexpensive devices with no internet connectivity providing responses in milliseconds.
Visual technology approach does not require human engineered ad-hoc algorithms to extract the discriminative features in an image to make accurate predictions. Our algorithms are able to learn how to extract these meaningful features from the input using only the provided training data. This makes them easy to adapt to problems in any domain and evolve to new capabilities.
This is one area where a heavy level of automation is required with intelligence embedded to robots. With space exploration becoming more commercialized and availability to local public is also in its vicinity a major factor that is helping achieve this feat is through AI induced robotics right from manufacturing, assistance in exploration, servicing, space debris cleanup, virtual world and augmented reality systems, supervised autonomous systems.
One example would be machine vision using machine learning for Rocket landing. With the usage of reusable rockets a major breakthrough in space exploration. The feat was achieved using a convex optimization algorithm fed into a machine learning model using computer vision data wherein the system could accurately guide the rocket for a perfect landing considering all the factors incorporated. The accuracy also keeps becoming better with more learning.
Soon, spacecraft may operate using only artificial intelligence and machine learning algorithms. As in the past, it is technological innovations that will enable humans to go “where no man has gone before.” For the immediate future, those innovations will continue to emerge from machine learning.
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