Výsledky vyhledávání

Akademický článek

Comparative Study on the effects of Urban Heat Islands using Remote Sensing and Geographical Information System for the Salem district, India

Autor: Sivakumar V.L., Raju Anand, A.V. Sundaram

Publikováno v: E3S Web of Conferences, Vol 491, p 02042 (2024)

The ecology and all of its components are suffering greatly as a result of the unchecked speed of development. At this rate, environmental degradation will have an impact on humanity and associated fields. In order to prevent the consequences of expa

Externí odkaz: https://doaj.org/article/de75c076e534492f8612eb00aee5bd78

Zobrazit plný text záznamu

Akademický článek

Study of Forest Fire Severity through Normalized Burn Ratio Analysis using Remote Sensing

Autor: Sivakumar Vidhya Lakshmi, Raju Anand, A.V. Sundaram

Publikováno v: E3S Web of Conferences, Vol 491, p 01027 (2024)

Forest fires are a type of natural catastrophe that poses a risk to the vegetation and fauna of the hill stations. Due to the presence of vast enormous areas of land adorned with aged trees, vegetation, and wild life, safeguarding the ecosystem is bo

Externí odkaz: https://doaj.org/article/d3cddd6e2eb84de085181a8899a054cc

Zobrazit plný text záznamu

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Conference

Tree counting and classification of different level of trees using machine learning algorithms.

Autor: Raju, Anand

Publikováno v: AIP Conference Proceedings; 2024, Vol. 2915 Issue 1, p1-5, 5p

Zobrazit plný text záznamu

Akademický článek

Airborne Hyperspectral Imagery for Band Selection Using Moth–Flame Metaheuristic Optimization

Autor: Raju Anand, Sathishkumar Samiaappan, Shanmugham Veni, Ethan Worch, Meilun Zhou

Publikováno v: Journal of Imaging, Vol 8, Iss 5, p 126 (2022)

In this research, we study a new metaheuristic algorithm called Moth–Flame Optimization (MFO) for hyperspectral band selection. With the hundreds of highly correlated narrow spectral bands, the number of training samples required to train a statist

Externí odkaz: https://doaj.org/article/7377017c50544e4c89c664391287dd4f

Zobrazit plný text záznamu