Aventior has signed a long-term partnership with ESRI to become an ESRI marketplace provider for AI and Deep Learning Solutions.
Aventior is excited to announce the launch of its Vehicle Detection Deep Learning Algorithm on the ESRI marketplace. Detecting vehicles and determining their count from satellite imagery is a complex and time-consuming approach. For handling such intricate tasks, deep learning models offer the superior capability to learn such complex workflow semantics and produce exemplary results. This Deep Learning based process block is capable of detecting and counting various vehicles such as Cars, Vans, Pickup Trucks and Buses, in satellite images in an automated fashion, thus reducing effort and time for analysis. Aventior’s Vehicle Detection Deep Learning model delivers exemplary performance on 30 cm resolution satellite imagery.
Aventior’s Vehicle Detection Model results can be used for a variety of purposes, including base map preparation, humanitarian aid, disaster management, and transportation planning. Applications range from taxation, urban planning, public works, visualization, simulation to a wide range of suitability analysis applications.
For more information on our service offerings please contact us at [email protected] or visit our webpage https://aventior.com/vehicle-detection-esri-release/
Artificial Intelligence (AI) is the tech buzz phrase of 2020.
Amazon Echo ShowThe current range-topping device with Alexa allows you to do everything from checking relatives in the next room or on the other side of the world to buying pants from Amazon to stay away from your daily schedule.The 7-inch screen allows you to make video calls to other show users, which is great, but can also get a brief peak, for example, the appearance of an elderly relative (with their permission, of course) should disturb them.
Great for peace of mind.Not only does Amazon’s Alexa AI provide you with music based on advanced voice search terms — “play sad pop songs from the 1980s,” for example — it also learns to understand you better, the more you use it.2.Kuri Home RobotAlthough Kick starters and Prototypes have come and gone, we haven’t seen many Home Assistant robots come into the mainstream.
With the advancement of AI technology and reduced hardware costs, it may be time for robots to truly be useful around the home, and Kuri is leading the charge.Music can be played by these robots, take photos and videos on the fly, answer your questions, and engage in some conversation, thanks to the AI smarts hidden behind its mechanical eyes.
The gadget also includes mapping sensors, which allow the Kuri to move around the dining room tables and chairs in the living room.Two other areas where the face and voice recognition robot’s artificial intelligence features take effect, so Kuri knows who is talking and can change its responses.To read about: The Revolution Of Artificial Intelligence TechnologyYou can configure Kuri via the affiliate app (to wake you up in the morning), as well as review photos and videos that Kuri has captured while traveling around your home.
By learning when and how to use your heating, the Nest Thermostat can help you use your heating more economically and efficiently.Allow it to use your phone’s location, and the nest automatically turns off heating when other members of your home are gone.
Let’s look at the concepts that dominate conversations about machine learning and deep learning and how both are different from each other.Read Full Article: https://bit.ly/3hPin7V
It is important as it helps to identify existing or/and potential hazards.
Many of these lines are inaccessible due to a lack of transportation and geographical locations.
The undetected faulty gas lines and power lines had led to a forest fire.
They also face certain limitations such as inaccessible terrain, contact with high-voltage power lines, hazardous chemicals emission, and more.Using Drones for Utility InspectionsDue to the above, many companies have started to use drones as the inspectors can survey the structures or lines from a safe distance and can cover difficult terrains & conditions with ease.
Few examples of utility inspections carried out using drones are:Power transmission line– to identify foliage encroachment, sagged wires, fuels buildup that leads to forest firesVertical constructions– to check signs of irregularities and damageBridges & overpass– to check signs of damage or cracksWater systems– to identify leakages, management of vegetationDams– to check structural defects and identify the repairs neededDrones improve the quality of such inspection as it allows the inspectors to conduct frequent inspections and to collect more data.
Thermal imagery, hyperspectral, color, light detection & ranging are the sensors used.
With such an extensive amount of buzz occurring since the most recent couple of days, it is inescapable to dodge, what machines procuring mean, and even what all could MACHINE LEARNING help us with!With Machine Learning or the errand of causing machines to realize what all could be the conditions or the occasions wherein, a machine could work things out, according to the circumstances, and the typical way any human would carry on, as any procedure of Machine Learning instructional exercise, would be working out!Deep learning is a piece of a more extensive group of Machine Learning strategies dependent on counterfeit neural systems.
The procedure can some of the time require area information about a given issue.To all the more likely comprehend include designing, think about the accompanying model.In the land business, the area of a house significantly affects the selling cost.
A deep learning calculation will filter the information to look for highlights that correspond and consolidate them to empower quicker learning without being unequivocally advised to do as such.This capacity implies that information researchers can at times spare a very long time of work.
On different occasions, information naming may require the decisions of deeply gifted industry specialists, and that is the reason, for certain enterprises, getting excellent preparing information can be over the top expensive.To make right, self-sufficient choices, the calculation requires a huge number of well-clarified pictures where diverse physical oddities of the human body are obviously marked.
Given that around 4-5 pictures can be dissected every hour, legitimate naming of all pictures will be costly.With deep learning, the requirement for well-named information is caused outdated as deep learning calculations to exceed expectations at learning without rules.
In the model over, a deep learning calculation would have the option to identify physical irregularities of the human body, even at prior stages than human specialists.Proficient at Delivering High-quality Results People need rest and fuel.
