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Toplam 31 adet sonuçtan 20 tanesi görüntülenmektedir.

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Özel Aralık Girişi
Ransomware Detection and Classification using Ensemble Learning: A Random Forest Tree Approach
2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM), 26 Ekim 2023
SHAYEA IBRAHEEM ABDULLAH MOHAMMED
Ibraheem Abdullah Mohammed Shayea Tam metin bildiri wireless communication
Analysing the Determinants of Surface Solar Radiation with Tree-Based Machine Learning Methods: Case of Istanbul
Pure and Applied Geophysics, Nisan 2024, ISSN: 0033-4553
GÜVEN DENİZHAN
Denizhan Güven Özgün Makale Surface solar radiationMachine learningForecastingRandom forest
Monthly Water Consumption Modelling of The Metropolitan City of Istanbul Using Hybrid Wavelet Transform and Random Forest
8TH INTERNATIONAL "BAŞKENT" CONGRESS ON PHYSICAL, ENGINEERING, AND APPLIED SCIENCES, Ankara/TÜRKİYE, 4 Şubat 2023
EKMEKCİOĞLU ÖMER
Ömer Ekmekcioğlu Özet Bildiri
Seed texture classification by random forest and neural networks
Signal Processing and Communications Applications Conference (SIU), 2017 25th, Antalya/TÜRKİYE, 15 Mayıs 2017, s. 1-4
AYGÜN SERCAN,YALÇIN HÜLYA,GÜNEŞ ECE OLCAY
Ece Olcay Güneş Tam metin bildiri
A benchmarking: Feature extraction and classification of agricultural textures using LBP, GLCM, RBO, Neural Networks, k-NN, and random forest
2017 6th International Conference on Agro-Geoinformatics, Fairfax, VA, USA/AMERİKA BİRLEŞİK DEVLETLERİ, 7 Ağustos 2017, s. 1-4
AYGÜN SERCAN,GÜNEŞ ECE OLCAY
Ece Olcay Güneş Tam metin bildiri
Evaluating the potential of multi-temporal Sentinel-1 and Sentinel-2 data for regional mapping of olive trees
INTERNATIONAL JOURNAL OF REMOTE SENSING, Vol. 44, No. 23, Kasım 2023, s. 27, ISSN: 0143-1161
AKÇAY HAYDAR MUHAMMED, KAYA ŞİNASİ, SERTEL ELİF, AKSOY SAMET, JADU DASH
Elif Sertel Özgün Makale Olive classification Sentinel optical and radar data data fusion random forest Google Earth Engine
Development of an early warning system for higher education institutions by predicting first‐year student academic performance
Higher Education Quarterly, Ocak 2024, ISSN: 0951-5224
ÇIRAK CEM RECAİ,AKILLI HAKAN,EKİNCİ YELİZ
Cem Recai Çırak Özgün Makale machine learningdata miningclassification algorithmsrandom forestperformance evaluationstudent success
Evaluating the potential of multi-temporal Sentinel-1 and Sentinel-2 data for regional mapping of olive trees
INTERNATIONAL JOURNAL OF REMOTE SENSING, Vol. 44, No. 23, Kasım 2023, s. 27, ISSN: 0143-1161
AKÇAY HAYDAR MUHAMMED, KAYA ŞİNASİ, SERTEL ELİF, AKSOY SAMET, JADU DASH
Samet Aksoy Özgün Makale Olive classification Sentinel optical and radar data data fusion random forest Google Earth Engine
Evaluating the potential of multi-temporal Sentinel-1 and Sentinel-2 data for regional mapping of olive trees
INTERNATIONAL JOURNAL OF REMOTE SENSING, Vol. 44, No. 23, Kasım 2023, s. 7338-7364, ISSN: 0143-1161
AKÇAY HAYDAR, AKSOY SAMET, KAYA ŞİNASİ, SERTEL ELİF, DASH JADUNANDAN
Şinasi Kaya Özgün Makale Olive classification Sentinel optical and radar data data fusion random forest Google Earth Engine
Assessment of water quality and aquatic diversity of an open-pit gold mine area using random forest algorithm with Google Earth engine
Fen Bilimleri Enstitüsü, İstanbul Teknik Üniversitesi, 2020
ŞENER ALKAN
Esra Erten Tez Yüksek Lisans Tamamlandı
Data-Driven Modeling of Lateral and Cracking Loads in Confined Masonry Walls Using Machine Learning
Buildings MDPI, Vol. 14, No. 4016, Aralık 2024, ISSN: 2075-5309
BİLE HAMZA MAHAMAD,GÜLER KADİR,GÜLER KADİR
Kadir Güler Özgün Makale confined masonry walls; machine learning; extreme gradient boosting; random forest; lateral load capacity; cracking load; extremely randomized trees; empirical models

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