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Labeled image data is important for AI-powered applications. Let our in-house teams make sure that it purrr-fact for your algorithm needs.
FTo meet specified industry standards and procedures, FutureBeeAI generates a variety of image annotations from the raw photos in the most precise methods.
Our workforce of annotators includes individuals across all cultures and industries. We can deliver over 97-99% accurate labels because of our supervision and years of experience.
Our QA and review process involves the manual investigation of annotated images in various stages. Data security in the system is maintained by our efficient process.
AI-based facial recognition technology can help identify the owner of the vehicle. AI-enabled automotive can help get custom settings in vehicles based on the user experience.
AI-enabled automotive can identify and track the lane and reduce the burden on drivers to keep the eye on the road on a long journey!
Path hole detection can warn the driver while approaching the hump or the path hole and reduce the chances of accidents.
Computer vision-based visual inspection models can assist in claiming insurance in no time with the utmost accuracy.
AI-enabled autonomous vehicles can not only drive from place A to B without any manual assistance from the driver but can do self-parking and lane tracking.
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We can use UAVs aka drones to capture the soil and crop and build an AI model that can detect the quality and quantity along with crop and soil health.
AI can do high labour-intensive tasks like crop maturity monitoring as well as using high-level computer vision models which can classify the crop based on various criteria.
A computer vision-based AI model which is pre-trained for identifying various plant diseases can help farmers in the identification and prevention of various plant diseases from an early stage.
AI-enabled computer vision models can keep eye on livestock. It can count and track the behaviour of livestock to identify their health.
CV model can not only detect the disease but can also help in prevention by identifying target areas and spraying fertilizers using UAVs.
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AI can analyse various medical imagery like ultrasound, MRI, and X-rays and detect various diseases from the graphical information and can assist doctors.
Surgical robots can aid with surgery with sub-millimetre precision by identifying the repeated activities inside the surgical operation.
NLP & OCR-based AI applications can retrieve relevant information from medicine images and medical documents. The text can also be translated into the user's native language.
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AI can aid in the automation of various processes. Users can click the image of the cheque and upload it to bank server to submit the cheque.
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Automated check-out without the need for cash, facial recognition payment, the opportunity to see 3D products at home, and other features are all possible in retail settings with AI integration.
AI image recognition technology can help us identify several comparable goods at once and provide the precise amount for each, allowing shops to manage their inventory and orders.
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Artificial intelligence-enabled video analytics can assist in detecting any illegal behaviour or threat in a fraction of a second, making it a proactive security solution.
AI-enabled video analytics can aid in traffic management and improve road safety by detecting: no-helmet and triple riding detection, wrong-way driving, and over-speeding detection.
Using computer vision techniques, each item in a frame can be identified and segmented and then matched against a list of predefined categories to aid in safety.
AI can assist in the post-incident investigation, machine learning algorithms can be employed for colour conversion, regeneration, and comparison between two video backdrops.
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The AI-powered computer vision, NLP, technology enables 3D views of properties without stepping foot in the property area. It can assist with zoom-in, spoken notes, and panorama view functions.
Using a video analytic tool, property conditions can be analyzed and solutions for maintenance can be predicted. It can prevent a lot of labour, time, and expense.
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Our diverse Human In The Loop community drives better control over quality standards and more than 99% of accurate and precise annotation within a definite time span. Explore more about our multilingual annotator community 👇
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Get the dataset from the store Annotate it with help from our community OR Get ready-to-deploy structured data (with annotations) directly from our store.
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