Digica

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Overview

$10,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

50 - 249

Employees

2009

Year Founded

ABOUT DIGICA

Deep Learning in Computer Vision, Machine Learning

Digica is an autonomous company specializing in Data Science and Artificial Intelligence. We assist our clients by integrating the latest Data Science and AI technologies into their systems and products, resulting in tailored solutions. Our knowledgeable team, backed by our own comprehensive research program, ensures that the most effective methods are utilized in every scenario. We possess significant expertise in image processing, including Deep Learning for Computer Vision and advanced commercial applications of Synthetic Imaging. Our services also encompass Large Language Models, Audio Analysis, and Predictive Maintenance. As a collective of engineers and engineering managers, we excel in the practical implementation of Artificial Intelligence and Machine Learning. We foster innovation by utilizing Machine and Deep Learning techniques. If you believe your product or solution could benefit from AI but find the process daunting or risky, our experienced team is ready to help you navigate these challenges and introduce you to the era of "new electricity."

Languages Spoken

EnglishPolish

HIGHLIGHTS

$10,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

50 - 249

Employees

2009

Year Founded

Services

Focus

Industries

Clients

Services Provided

14% Machine Learning Model Development

13% Computer Vision Solutions

3% AI Strategy & Roadmap Consulting

3% LLM Integration & Prompt Engineering

17% Custom Web Application Development

17% API Development & Integration

23% AI Strategy & Roadmap Consulting

10% Operational Process Consulting

About the Team

OUR STORY

Digica approached the fresh produce retail company's project as a collaborative partnership, reflecting their preferred working style. They developed a tailored, comprehensive operational software system from the ground up, managing every phase from discovery through testing to implementation. Throughout the process, Digica demonstrated flexibility and dedication, promptly resolving any issues that arose. Their commitment to the project is evident in consistent communication, including frequent Zoom meetings and weekly commercial updates, fostering transparency and trust. This personalized and attentive approach has been well-received by the client, highlighting Digica's investment in delivering a reliable, customized software solution that supports the client's operational needs effectively.

Portfolio

DL in detection of microscopic tissue features

Unknown

Digica was assigned the job of identifying features in microscopic tissue images, which are digitized slides viewed under a microscope. These slides were treated using the H&E staining method. The project was unusual because of the limited number of labeled examples and the target images had a resolution in the thousands of megapixels. The task required either segmenting or detecting features like cell nuclei (shown in the figure on the right) and microvessels. The technologies used included PyTorch, TensorFlow, and cutting-edge CNN architectures.

Detecting people in masks on thermal images

Unknown

Facial recognition technology has significantly advanced, but during the COVID-19 pandemic, systems equipped with infrared cameras struggled to identify individuals wearing masks. Our solution involved using RGB images of masked individuals alongside thermal images generated through an in-house adaptation technique. After training the detector with these image sets, it was able to recognize people in masks and relay their locations to the temperature-measuring algorithm. We referred to the outcome as an "automated remote thermometer," which assisted scanning stations in curbing the spread of COVID-19. Results showed an improvement in recall from 90% to over 99%. The technologies used included TensorFlow, MobileNet, and SSD.

Deep learning in CV in optimizing surgical process

Unknown

Digica developed an application that enables medical staff to automatically recognize surgical trays and their contents. This application utilizes deep learning algorithms in computer vision and incorporates the proprietary Enigma AI tool suite designed for working with synthetic data. Prior to surgery, team members can take a photo of a surgical tool tray with their mobile phone to receive alerts about any missing instruments or implants. After the procedure, they can identify which tools and implants were used by noting what has been removed from the trays. To accurately reflect real-world conditions, images of the objects must be captured from various angles, with different lighting, and sometimes obscured by other items.

7 more projects