Computer Vision and Machine Learning Solutions

  • Synaptiv
  • ParcsGabon
  • University of Stirling
  • WWF
  • wcs

Fast Development

1 week from concept to working prototype

object detection

Object Detection

See more than human auditors are capable of

image classification

Image Classification

Automate tasks that once took many hours

satallite

Satellite Image Analysis

25 cm maximum satellite image resolution

Our Work

Case StudiesSee more

Preserving Wildlife With Computer Vision
Smart Cameras – Insights Into Ecosystems
Leveraging Citizen Science Data
Monitoring The Arctic Ocean
  • Computer Vision
  • Open Source
  • Wildlife Conservation

Preserving Wildlife With Computer Vision

Mbaza is used in the national parks of Gabon to help protect and monitor their pristine ecosystems. It is powered by image classification models, allowing the ecologists and park rangers to tap into insights from the data collected by camera traps. Using their existing equipment, they can process the data within a day. Without the tool, this typically took a month. Read more

Mbaza Golden Cat - Computer Vision Camera Trap
  • Computer Vision
  • Realtime Image Classification
  • Wildlife Conservation

Smart Cameras – Insights Into Ecosystems

With smart cameras, it becomes feasible to monitor remote ecosystems in real-time. This makes it possible to, e.g., alert farmers in Central Africa that Elephants are about to intrude in their fields before it happens. We have prepared Computer Vision models which were utilized in the smart cameras tested in Central Africa. Read more

Mbaza elephant - smart cameras
  • Citizen Science
  • Computer Vision
  • Ecosystem Monitoring

Leveraging Citizen Science Data

Partnering with dendrologists, we studied the life cycle stages of plants from Polish forests. Utilizing citizen science platforms allows for large-scale, high precision monitoring of the shifts in ecosystems’ synchrony as it is affected by climate. Read more

Flowering plant take by citizen scientist - making the most of citizen science imagery using computer vision
  • Computer Vision
  • Data4Good
  • Image Segmentation

Monitoring The Arctic Ocean

The vitality of plankton is a crucial window into the health of the Arctic ocean. We have developed methods of assessing the nutritive value of plankton using Image Segmentation, which opens the possibility of monitoring the Arctic oceans’ ecosystem on a large scale. This is particularly important in the era of accelerated shifts caused by the climate crisis. Publication coming soon

Copepods from the Arctic Ocean - monitoring health of ocean with machine learning

Testimonials

What Our Clients Say

Grzegorz Jakacki

CTO at Lasy i Obywatele

I can attest to exceptionally professional and effective workflow and great project management at Appsilon.

Robin Whytock

Research Fellow, University of Stirling
University of Stirling

[They're able to] understand project needs and to develop innovative solutions that we had not previously envisioned.

Profile image of Enginious CEO, Piotr Kocel

Piotr Kocel

CEO at Enginious
Enginious company logo

We’re impressed that they are results-oriented.

Prof Frederic Maps profile

Frederic Maps

Associate Professor, Université Laval
Université Laval logo

Their genuine curiosity and impressive ability to adapt to our needs were outstanding!

Matt Lewis

CEO, Data Analytics Platform Provider
Projects

We were impressed with the professionalism of the team and their project management style.

  • Appsilon 20+ perfect Clutch reviews
  • Deloitte logo
  • rstudiologo
  • strongleaders

Research

Research Papers from Team Appsilon

Real-time alerts from AI-enabled camera traps using the Iridium satellite network: a case-study in Gabon, Central Africa

10 November, 2021

Read Paper

Robust ecological analysis of camera trap data labelled by a machine learning model

19 February, 2021

Read Paper

Blog

Discover latest articlesSee more

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Gift bag we received from the organizers, including the prize our team won.

Contact Us

Reach Out. We'll respond within 24 hours

Jędrzej Świeżewski, PhD
Jędrzej Świeżewski, Ph.D.
Senior Data Scientist