DevicoAI

Computer Vision сompany

Computer
vision services

Unlock the potential of your visual data and
accelerate growth and efficiency

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What is
computer vision?

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Computer vision is a subset of artificial intelligence (AI) that enables systems to interpret and make decisions based on visual data. It's like teaching a computer to see and understand the world similarly to how humans do.

Just as you recognise a familiar face in a crowd, computer vision algorithms can identify objects in images, analyse medical scans, or enable autonomous vehicles to navigate safely.

Why choose DevicoAI for сomputer vision services?

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High retention rate

96%

Our dedicated team ensures consistent support and expertise, significantly above the industry average of 80%.

Wide expert network

3000

Access to over 3000 engineers and AI experts.

Proven track record

500,000

Over 500,000 man-days successfully delivered.

Support

24/7

Highly experienced management team available around the clock.

Gather accurate data

Computer vision adoption growth is expected to reach 270% over four years

Computer vision development process

01

Data collection

Gathering relevant data from various sources.

Data collection

02

Data preparation

Cleaning and organizing data to make it suitable for analysis.

Data preparation

03

Model training

Using algorithms to train a model on the prepared data.

Model training

04

Model evaluation

Assessing the model's performance to ensure it meets the desired criteria.

Model evaluation

05

Model deployment

Implementing the model in a real-world environment.

Model deployment

06

Monitoring and maintenance

Continuously tracking the model's performance and updating it as necessary.

Monitoring and maintenance

How businesses are using
computer vision

Healthcare

Computer vision can analyse medical images for disease detection and treatment planning. It significantly improves diagnostic accuracy and speeds up the diagnosis process, leading to better patient outcomes.

Use cases:

  • Disease detection from medical imaging.
  • Surgical assistance with real-time image analysis.
  • Patient monitoring and anomaly detection.
  • Automated analysis of pathology results.
Finance & insurance

Financial institutions use computer vision for facial recognition to enhance security and automate processes like cheque deposit via mobile apps. This technology also helps in preventing fraud and ensuring compliance with regulations.

Use cases:

  • Facial recognition for secure customer authentication.
  • Automated processing of financial documents.
  • Detection of fraudulent activities.
  • Enhanced compliance with KYC (Know Your Customer) regulations.
Retail

Retailers leverage computer vision for personalised marketing and enhancing customer experiences. This technology is used to analyze customer behavior, manage inventory, and even create cashier-less stores.

Use cases:

  • Customer behavior analysis for personalized marketing.
  • Automated checkout systems.
  • Real-time inventory management.
  • In-store security and theft prevention.
Manufacturing

In manufacturing, computer vision helps with quality control and predictive maintenance. It ensures products meet quality standards and helps in maintaining equipment by predicting failures before they occur.

Use cases:

  • Automated quality control inspections.
  • Predictive maintenance of equipment.
  • Monitoring production lines for efficiency.
  • Safety compliance and hazard detection.

Be resilient and competitive

From smart automation to real-time analytics -
utilize computer vision with DevicoAI

Сore capabilities of
computer vision

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Image recognition

Identifying objects and features in images. It helps in applications like photo tagging, medical image analysis, and surveillance.

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Object detection

Locating and identifying objects within an image or video. It’s used in security systems, autonomous vehicles, and industrial inspection.

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Facial recognition

Detecting and recognising human faces in images and videos. It’s widely used for authentication, security, and personalised user experiences.

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Video analysis

Analysing video content to detect and track objects or activities. It’s crucial for surveillance, activity recognition, and event detection.

Advanced computer vision techniques

Criteria

Convolutional Neural Networks (CNNs)

Generative Adversarial Networks (GANs)

Transfer Learning

Definition

A class of deep neural networks, most commonly applied to analysing visual imagery.

A class of machine learning frameworks where two neural networks contest with each other to create new, synthetic instances of data.

Utilising a pre-trained model on a new, related problem.

Goal

Automatically and accurately recognise patterns in images.

Generate new, realistic images by learning the distribution of the original dataset.

Leverage existing models to reduce training time and improve performance on new tasks.

Algorithms

Convolutional layers, pooling layers, fully connected layers.

Discriminator and generator network.

Fine-tuning pre-trained models, domain adaptation.

Data Requirement

Requires large amounts of labelled image data.

Requires substantial data for both networks to learn the data distribution.

Requires less data than training a model from scratch, using pre-trained models.

Advantages

High accuracy in image classification tasks, ability to capture spatial hierarchies in images.

Capable of generating high-quality synthetic images, useful for data augmentation.

Significantly reduces training time and resources, improves performance with less data.

Applications

Image classification, object detection, facial recognition, medical image analysis.

Image generation, data augmentation, image-to-image translation.

Custom image classification, object detection, semantic segmentation.

Techniques

Backpropagation, activation functions (ReLU), dropout regularisation.

Adversarial training, optimisation of generator and discriminator.

Model fine-tuning, transfer learning architectures like VGG, ResNet.

Get in touch

Drop us a line about your project and we will contact you within a business day

Our locations

New York

HQ

521 Fifth Ave, NY 10175

+1 805 491 9331

London

Sales

9 Brighton Terrace, SW9 8DJ

+44 1922 214429

Warsaw

R&D

Towarowa 28, 00-847

info@devico.io

Lviv

R&D

Uhorska str. 14, 79034

info@devico.io

Questions & answers

With advanced expertise, DevicoAI helps your company to exceed human-level identification accuracy, fast-tracking your operational workflow to turn a concept into reality.

The cost depends on the complexity of the project, the technologies involved, and the scope of the solution. We offer tailored pricing based on your needs and goals to ensure you get the best value for your investment.

This varies depending on the specific project and set goals. DevicoAI can help you assess your data readiness and explore strategies for maximizing its value. If you can’t provide a ready data set, we can use our field data collection for model development.

Yes, we work closely with your internal teams to integrate Computer Vision algorithms into your existing infrastructure and ensure that the transition is smooth and efficient.

To begin, we need to understand your business objectives, access relevant data, and any system specifications necessary for integration.

Implementing computer vision involves handling vast amounts of unstructured data. Additionally, it's essential to ensure that the solution scales effectively as your business grows. DevicoAI offers comprehensive support to ensure a smooth integration process, tailored to your business needs.

We provide comprehensive support throughout the entire lifecycle of your computer vision project: initial consultation, data collection and preparation, algorithm selection, model training, deployment, and ongoing maintenance. Our goal is to ensure the success of your computer vision initiatives.

The timeline depends on the complexity and scope of the project. On average, custom Computer Vision models can take anywhere from a few weeks to several months.

Yes, we provide ongoing support and maintenance to ensure that the developed model continues to meet your business needs and adapts to any new challenges.

We follow strict compliance protocols throughout the ML process, including data anonymisation, secure storage, and regular audits to maintain compliance with industry standards and regulatory requirements.