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AI in Robotics
//INDUSTRIES
AI IN ROBOTICS
Artificial Intelligence (AI) is transforming the logistics industry by optimizing processes, enhancing efficiency, and improving decision-making. Annotation for robotics involves labeling and annotating data to facilitate the training and development of robotic systems.
DATA ANNOTATION FOR INCORPORATING AI IN ROBOTICS
Object Recognition and Detection
Annotation involves labeling objects in images or sensor data captured by robots, enabling them to recognize and detect objects in their environment. This includes labeling objects such as tools, parts, obstacles, and other relevant items.
Semantic Segmentation
Annotation assigns pixel-level labels to images or sensor data, distinguishing between different classes of objects and background elements. This helps robots understand the semantic meaning of each pixel in the scene, enabling them to navigate and interact with their environment more effectively.
Human-Robot Interaction
Annotation involves labeling human gestures, expressions, and actions to enable robots to understand and respond to human commands and interactions. This includes annotating gestures, speech, and facial expressions to facilitate natural and intuitive communication between humans and robots.
Anomaly Detection
Annotation involves labeling anomalous or unexpected events in sensor data to enable robots to detect and respond to abnormalities in their environment. This includes annotating sensor data with information about anomalies such as sudden obstacles, environmental changes, or equipment failures.
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//Industries
INDUSTRIES WE SERVE
RETAIL
Assisting the retail and e-commerce sectors by providing training data to optimize their in-store operations through the implementation of artificial intelligence (AI).ROBOTICS
3D object detection finds extensive application in robotics, particularly to prevent collisions with dynamic entities such as humans, animals, and other objects.AGRICULTURE
Supporting agriculture through computer vision training data involves facilitating the identification of product defects, sorting produce, managing livestock, assessing soil quality, implementing fertilizer applications, and fine-tuning genetic conditions.INSURANCE
Preparing training data to integrate AI into insurance procedures for tasks such as risk assessment, fraud detection, underwriting and minimizing human error.HEALTHCARE
Incorporating annotations and accurate labeling within AI systems is crucial for uncovering connections within genetic codesand enhancing efficiency in healthcare processes.SECURITY & SURVEILLANCE
Facilitating the integration of AI into cameras and sensors enables the detection of potential risks at workplaces, airports, and industrial sites. This involves incorporating computer vision technology into security and surveillance systems.SELF-DRIVING
Bounding boxes serve to annotate the surroundings of a vehicle, aiding in the detection of various objects including pedestrians, vehicles, traffic signs, and barriers.LOGISTICS
Logistics represents one of the growing areas of artificial intelligence application. We specialize in annotating images of goods to generate high-quality training data utilized in logistics.AUTONOMOUS FLYING
Simplifying and broadening access to AI implementations for automated or assisted flight can be achieved by leveraging image annotation conducted at the backend using training data specifically tailored for autonomous flying.