Manufacturing

AI technologies are used to boost the productivity and quality of production
Manufacturing and construction are highly traditional fields. These are the domains that often see better equipment, more powerful machines, and improved technology, the innovations are far less seen. Also, due to the traditional nature with limited room for innovation, the manufacturing also 'lives by' the challenges regularly.

New technology in manufacturing is the computer vision technology that enables the machine to 'learn visually.'

Though, with the advancement in the field of robotics, AI, machine learning, the manufacturing industry is about to witness disruption at a global scale.

Tagias Manager helps you create a good technical task for the data or markup that needs to be performed. So that you get a training dataset that gives real results and a low error rate.
RETAIL
CASES

Use cases

Image annotation

Fully automated product assembly and management processes
Identifying defects in products and packages more accurately and faster
Vision-guided robots
Product
assembly
Defect
reduction
Controlling and determining the certain objects in manufacturing process
Tracking components and packages at all stages of development
Packaging inspection
Barcodes and text labels scanning
Machine vision inspection systems for quality control and packaging standards
Inventory Management
Maintaining inventory status, automating and alerting managers
Bounding boxes
Classification
Keypoints
Polygons
Lines
Semantic segmentation
Bounding box annotation
Bounding boxes
The most common type of data annotation. Bounding boxes are mainly intended to detect objects, delineating their borders with transparent rectangles. Bounding boxes are applied in almost all industries of the data labelling market.
Images classification
Classification
This method is used to determine the presence of an object in the image. A specific label is assigned to each image. Image tagging helps train AI to recognize objects' classes.
Keypoints annotation
Keypoints
This type of annotation uses dots across an image to identify an object or its details/parts. Keypoints are applied mostly with facial recognition, body parts, and postures.
Polygons annotation
Polygons
Polygons are used to determine an object's shape and location with maximum precision while avoiding additional noise. Polygon annotation is applied in almost all industries.
Lines annotation
Lines
Lines annotation is used for detecting and recognizing lanes. This type of annotation is applied mostly in the automotive industry to make self-driving cars safe.
Semantic segmentation
Semantic segmentation
A data labelling method where objects are delineated in the image at the pixel level, depending on class. It's called semantic segmentation because each pixel has semantic meaning. Segmentation is usually applied in the automotive industry.