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Image Annotation Services
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// AI Image Annotation Services
For Computer Vision
Essdel offers a range of image annotation services tailored to meet the specific requirements of each client’s project. These services encompass bounding boxes, polygon annotations, keypoint annotation, LiDar, semantic segmentation, and image classification. Our dedicated team collaborates closely with clients to fine-tune the quality and efficiency of the task, ensuring the best possible cost-quality ratio throughout the iteration process. We strongly advise initiating with a sample batch to clarify instructions, address potential edge cases, and estimate task durations before scaling up to full batches.
// our services
IMAGE ANNOTATION SERVICES
01
2D BOUNDING BOXES
It delineates the borders of objects within a two-dimensional area through graphical depictions. These bounding boxes commonly find application in computer vision and machine learning endeavours to delineate regions of interest pertaining to objects.
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02
3D CUBOID ANNOTATION
This method is employed to detect and identify 3D objects present in images. It aids machines in determining the depth of various entities such as vehicles, individuals, buildings, and other similar objects.
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03
LANDMARK ANNOTATION
Businesses employ this method to ascertain the form and emotion of natural objects, such as facial features and emotions, by utilizing a sequence of points. Additionally, it aids in constructing precise datasets for delineating the shape of items of various sizes.
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04
SKELETAL ANNOTATION
This annotation method is utilized to emphasize body movement and alignment by connecting lines across the human body. Annotators use this method to link these lines with dots positioned at points of articulation.
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05
POLYGON ANNOTATION
This annotation method entails marking and sketching shapes on a digital image, facilitating the identification of objects within the image according to their position and orientation. It encompasses labeling images with irregular dimensions.
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06
SEMANTIC SEGMENTATION
Semantic segmentation, a technique in computer vision, is employed to segment images by classifying each pixel according to its semantic category. This technique involves dividing an image dataset to accurately identify and delineate all categories and classes present within the images.
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07
3D POINT CLOUD ANNOTATION
This method serves for detecting and identifying 3D objects depicted in images. It assists machines in gauging the depth of various objects including vehicles, people, buildings, and other entities.
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08
POLYLINE ANNOTATION
It is the labeling of lanes using splines. This technique is specifically utilized for validating Advanced Driver Assistance Systems (ADAS) during the training of autonomous vehicles.
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// our clients
We are Trusted
We are Trusted
15+ Countries Worldwide
Moonkle LTD,
Client of Company
"Very well thought out and articulate communication. Clear milestones, deadlines and fast work. Patience. Infinite patience. No shortcuts. Even if the client is being careless. The best part...always solving problems with great original ideas!."
SoftTech,
Manager of Company
"Patience. Infinite patience. No shortcuts. Very well thought out and articulate communication. Clear milestones, deadlines and fast work. Even if the client is being careless. The best part...always solving problems with great original ideas!."
Moonkle LTD,
Client of Company
"Very well thought out and articulate communication. Clear milestones, deadlines and fast work. Patience. Infinite patience. No shortcuts. Even if the client is being careless. The best part...always solving problems with great original ideas!."
SoftTech,
Manager of Company
"Patience. Infinite patience. No shortcuts. Very well thought out and articulate communication. Clear milestones, deadlines and fast work. Even if the client is being careless. The best part...always solving problems with great original ideas!."
// why choose us?
Why ESSDEL for Image Annotation Services?
Our team of experts employ there hands-on experience on various Image annotation methods, to help our worldwide clients.
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Guaranteed Quality Service
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Cost Effective Image Annotation
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Transparency
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Tailer-made Offerings
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Quality Support
//Industries
USE CASES FOR IMAGE ANNOTATION
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).
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ROBOTICS
3D object detection finds extensive application in robotics, particularly to prevent collisions with dynamic entities such as humans, animals, and other objects.
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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.
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INSURANCE
Preparing training data to integrate AI into insurance procedures for tasks such as risk assessment, fraud detection, underwriting and minimizing human error.
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HEALTHCARE
Incorporating annotations and accurate labeling within AI systems is crucial for uncovering connections within genetic codesand enhancing efficiency in healthcare processes.
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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.
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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.
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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.
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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.
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