all AI news
Evaluating Terrain-Dependent Performance for Martian Frost Detection in Visible Satellite Observations
March 20, 2024, 4:42 a.m. | Gary Doran, Serina Diniega, Steven Lu, Mark Wronkiewicz, Kiri L. Wagstaff
cs.LG updates on arXiv.org arxiv.org
Abstract: Seasonal frosting and defrosting on the surface of Mars is hypothesized to drive both climate processes and the formation and evolution of geomorphological features such as gullies. Past studies have focused on manually analyzing the behavior of the frost cycle in the northern mid-latitude region of Mars using high-resolution visible observations from orbit. Extending these studies globally requires automating the detection of frost using data science techniques such as convolutional neural networks. However, visible indications …
abstract arxiv behavior climate cs.cv cs.lg detection drive evolution features latitude mars martian performance processes satellite studies surface type
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)
@ HelloBetter | Remote
Doctoral Researcher (m/f/div) in Automated Processing of Bioimages
@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena
Seeking Developers and Engineers for AI T-Shirt Generator Project
@ Chevon Hicks | Remote
Senior Applied Data Scientist
@ dunnhumby | London
Principal Data Architect - Azure & Big Data
@ MGM Resorts International | Home Office - US, NV