I hold a PhD in physics from the University of Cambridge, and have significant R&D experience across academia and industry. Over the last ten years, I have been working in the space sector, applying my optical expertise in the design and manufacture of space-based telescopes, as well as specializing in Python-based image analysis and software development. I am a well-known authority in machine and deep learning techniques for processing satellite and aerial imagery, and am dedicated to education. I have created the satellite-image-deep-learning.com website, newsletter, YouTube channel, and Github organization to share my knowledge and build a community. As a strong proponent of the open-source software movement, I regularly contribute to Github and strive to make a positive impact in the developer community. I have had the opportunity to share my expertise by presenting at various Python conferences and have been invited as a guest on several podcasts, including the ZenML and Mapscaping podcasts. Through these opportunities, I am able to share my knowledge and passion for the industry, while also connecting with other like-minded individuals.
robmarkcole
Follow
Busy pythonizing
Tackling the worlds toughest challenges with AI & ML applied to satellite imagery
- London, UK
-
04:05
(UTC -12:00) - @robmarkcole
- in/robmarkcole
- @satellite-image-deep-learning
Pinned Loading
-
satellite-image-deep-learning/techniques
satellite-image-deep-learning/techniques PublicTechniques for deep learning with satellite & aerial imagery
-
fire-detection-from-images
fire-detection-from-images PublicDetect fire in images using neural nets
-
mqtt-camera-streamer
mqtt-camera-streamer PublicStream images from a connected camera over MQTT, view using Streamlit, record to file and sqlite
-
yolov5-flask
yolov5-flask Public archiveOfficial implementation at https://github.com/ultralytics/yolov5/tree/master/utils/flask_rest_api
-
HASS-plate-recognizer
HASS-plate-recognizer PublicRead number plates with https://platerecognizer.com/
-
coral-pi-rest-server
coral-pi-rest-server PublicPerform inferencing of tensorflow-lite models on an RPi with acceleration from Coral USB stick
Something went wrong, please refresh the page to try again.
If the problem persists, check the GitHub status page or contact support.
If the problem persists, check the GitHub status page or contact support.