It takes about 1M images of the same item in order for a computer vision product to reach 99% accuracy in identifying products in real time.
Model generation & confidence score of 98%
Model prediction speed 10ms - 1s
4x – 6x Faster than manual labelling
6x – 8x Cost saving
Next generation retail solutions across Industries
01. Autonomous Vehicles
03. Security & Surveillance
06. Medical Imaging
08. Retail Automation
Why choose DigitSquare?
Why does DigitSquare matter?
DigitSquare is an end-to-end Saas based platform for annotating, training, and automating the computer vision pipeline.
What is Annotation/Labeling?
Annotation is the technique through which we label data so as to make objects recognizable by machines.
What are different types of labeling DigitSquare supports?
Rectangle, Polygon, Point and Line.
What are all the industries you serve?
Any industry requirement specific to Image/Video processing use-cases.
Is installation required or can we open the admin portal in browser?
How quick/fast and accurate?
Depends on the training data set and accurate annotations.
Is coding required or can anyone access?
Tool can be accessed only if the license is purchased, Coding is not required, this tool is built for ML Engineers.
How is my data handled on DigitSquare?
DigitSquare complies to GDPR.
How it is used to build AI models?
- Using annotated data sets, if the data is not annotated well, there is an option to auto label, set hyperparameters and generate models.
- Models generated using globally available standard formats.
How machine learning and deep learning works for image annotation.
- Using annotated data sets, if the data is not annotated as well, there is an option to auto label, set hyper parameters and generate models.
- Models generated using globally available standard formats. (Pytorch, TensorFlow, ONNX etc).
What is synthetic data? Advantages/disadvantages of synthetic data? What are the different types?
- Synthetic Image generation is the creation of artificially generated images that look as realistic as real images.
- ML Engineers often require highly quantitative accurate, and diverse datasets to train and build accurate ML models.
- Synthetic data helps in reducing the costs of data collection and data labelling. In addition to lowering costs,
- synthetic raw data helps address privacy issues associated with sensitive real-world data.
- Types of Synthetic Data
- Text data: Synthetic data can be artificially generated text in natural language processing (NLP) applications.
- Tabular data: Tabular synthetic data refers to artificially generated data like real-life data logs or tables useful for classification or regression tasks.
- Media: Synthetic data can also be synthetic video, image, or sound to be used in computer vision applications.
Is DigitSquare subscription Tool?
Yes, based on customer request, DigitSquare can be enhanced. Our pricing really depends on what you need. Feel free to reach out to us at firstname.lastname@example.org for assistance.