Výsledky vyhledávání - "Nahian Ahmed"

Akademický článek

Classification of Deep-SAT Images under Label Noise

Autor: Mohammad Minhazul Alam, Md Gazuruddin, Nahian Ahmed, Abdul Motaleb, Masud Rana, Romman Riyadh Shishir, Sabrina Yeasmin, Rashedur M. Rahman

Publikováno v: Applied Artificial Intelligence, Vol 35, Iss 14, Pp 1196-1218 (2021)

One of the challenges of training artificial intelligence models for classifying satellite images is the presence of label noise in the datasets that are sometimes crowd-source labeled and as a result, somewhat error prone. In our work, we have utili

Externí odkaz: https://doaj.org/article/08dc29f18e2846a4b118526e066af91f

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Machine learning for predicting landslide risk of Rohingya refugee camp infrastructure

Autor: Nahian Ahmed, Adnan Firoze, Rashedur M. Rahman

Publikováno v: Journal of Information and Telecommunication, Vol 4, Iss 2, Pp 175-198 (2020)

Since the dawn of human civilization, forced migration scenarios have been witnessed in different regions and populations, and is still present in the twenty-first century. The current largest population of stateless refugees in the world, the Rohing

Externí odkaz: https://doaj.org/article/f75aff01e90644d0b65409049bc6e70d

Zobrazit plný text záznamu

Akademický článek

Artificial Neural Network and Machine Learning Based Methods for Population Estimation of Rohingya Refugees: Comparing Data-Driven and Satellite Image-Driven Approaches

Autor: Nahian Ahmed, Nazmul Alam Diptu, M. Sakil Khan Shadhin, M. Abrar Fahim Jaki, M. Ferdous Hasan, M. Naimul Islam, Rashedur M. Rahman

Publikováno v: Vietnam Journal of Computer Science, Vol 6, Iss 4, Pp 439-455 (2019)

Manual field-based population census data collection method is slow and expensive, especially for refugee management situations where more frequent censuses are necessary. This study aims to explore the approaches of population estimation of Rohingya

Externí odkaz: https://doaj.org/article/5a80bcfae9444904b52ec1e7b6b4c7e5

Zobrazit plný text záznamu

Akademický článek

Understanding the political ecology of forced migration and deforestation through a multi-algorithm classification approach: the case of Rohingya displacement in the southeastern border region of Bangladesh

Autor: Nahian Ahmed, M. Naimul Islam, M. Ferdous Hasan, Tamanna Motahar, Mohammad Sujauddin

Publikováno v: Geology, Ecology, and Landscapes, Vol 3, Iss 4, Pp 282-294 (2019)

Compared with numerous existing forced migration scenarios across the globe, migration from Myanmar to Bangladesh through southeastern border region is unique at least for three reasons – (i) very large number of migrants have been displaced to (ii

Externí odkaz: https://doaj.org/article/6e0adcd0604c4a49b540ac413b2875be

Zobrazit plný text záznamu

Akademický článek

Improving Spatial Agreement in Machine Learning-Based Landslide Susceptibility Mapping

Autor: Mohammed Sarfaraz Gani Adnan, Md Salman Rahman, Nahian Ahmed, Bayes Ahmed, Md. Fazleh Rabbi, Rashedur M. Rahman

Publikováno v: Remote Sensing, Vol 12, Iss 20, p 3347 (2020)

Despite yielding considerable degrees of accuracy in landslide predictions, the outcomes of different landslide susceptibility models are prone to spatial disagreement; and therefore, uncertainties. Uncertainties in the results of various landslide s

Externí odkaz: https://doaj.org/article/c2a5dcae50444cf5b624e88ac0589a29

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

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

Vyhledávací nástroje:

Upřesnit hledání