SciFroce Computer Vision

Computer Vision

Enhance your capabilities with computer vision solutions

You might be wondering: “What is computer vision?” Simply put, it is the processing of visual input by machine learning models to take actions based on the analysis and recommendations. Technologies like computerized face recognition, object movement tracking, and automated product quality control are among computer vision examples. At SciForce, computer vision stands at the core of competencies. We know how to grant more control and awareness for everyone: From indoor analytics for retailers to security solutions. Check out the latest computer vision applications that we are designing for businesses, considering privacy by default.

Problems we solve

Optical Character Recognition (OCR)

Transforming and analyzing scanned documents, including handwritten ones. Matching it with machine learning algorithms, you can enjoy navigating extracted data and applying it however you want.


We are a one-stop for any security solution tailored to the needs of our clients. Our services include video surveillance, access control, checkpoint security, theft detection, public health and safety, and homeland security.

Customer Behavior Tracking and Indoor Analytics

Analyze your customers' behavior and optimize the user experience to make it flawless, taking privacy into account. Our solutions for retailers help to minimize the time spent, increase sales, and optimize customer distribution within the store.

Public Health: Medical Images Analysis and Segmentation

Simplify the analysis of MRIs, CTs, and ultrasound images to reduce treatment costs and prevent false diagnoses. Computer vision also generates data for medical research, automating tasks and optimize time and efforts of professionals.

Automated Anomaly Detection in Agriculture

SciForce solves challenges modern agritech companies face with the help of farming innovations and computer vision algorithms and applications. Thus, our solutions can help detect plant diseases at early stages and enhance crop monitoring and analysis.

Quality Control

Computer vision facilities manufacturing in various ways like automated inspection of product defects, packaging quality, and assembly control. Reduce waste and increase efficiency.

Technology we use

technologyBig Data Platforms
Hadoop, Kafka, Hive
MongoDB, SQL
technologyProgramming Languages
Python, C++
PyTorch, Tensorflow
technologyCloud Platforms
AWS, Azure, Google Cloud Platform
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