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Toplam 12 adet sonuçtan 12 tanesi görüntülenmektedir.

A comparison of LSTM and GNN based session recommendation systems

Lisansüstü Eğitim Enstitüsü, İstanbul Teknik Üniversitesi, 2021

ÇAĞRI EMRE YILDIZ

Yusuf Yaslan Tez Yüksek Lisans Tamamlandı

A comparatıve analysıs of LSTM and XGBoost methods for day ahead electrıcıty prıce forecastıng

Enerji Enstitüsü, İstanbul Teknik Üniversitesi, 2020

CAHİT URAL KÜKNER

Ahmet Durmayaz Tez Yüksek Lisans Tamamlandı

Use of LSTM for Short-Term and Long-Term Travel Time Prediction

International Workshop on Knowledge-Driven Analytics Impacting Human Quality of Life (KDAH-CIKM), 22 Ekim 2018

İŞLEK İREM,ÖĞÜDÜCÜ ŞULE

Şule Öğüdücü Tam metin bildiri

Combining predictive base models using deep ensemble learning

JOURNAL OF INTELLIGENT AND FUZZY SYSTEMS, Vol. 39, No. 5, Ocak 2020, s. 6657-6668, ISSN: 1064-1246

ÖNER MAHİR, ÜSTÜNDAĞ ALP

Alp Üstündağ Özgün Makale Deep Learning Ensemble LearningLSTM

Magnetic Resonance Fingerprinting Using Recurrent Neural Networks

2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), No. null, 8 Nisan 2019, s. 1537-1540

ÖKSÜZ İLKAY,CRUZ GASTAO,CLOUGH JAMES R.,BUSTİN AURELİEN,FUİN NİCCOLO,BOTNAR RENE,PRİETO CLAUDİA,KİNG ANDREW P.,SCHNABEL JULİA A.

İlkay Öksüz Tam metin bildiri Magnetic resonance fingerprintingRecurrent Neural NetworksLSTMGRUParameter mapping

Vibration control of a pier pile using deep learning LSTM network

The Second International Conference on Applied Mathematics in Engineering (ICAME 2021), Balıkesir/TÜRKİYE, 1 Eylül 2021

BAYINDIR CİHAN, NAMLI BARIŞ

Cihan Bayındır Tam metin bildiri

Spectrum Occupancy Prediction Exploiting Time and Frequency Correlations Through 2D-LSTM

IEEE 91st Vehicular Technology Conference (VTC2020-Spring), Antwerp/BELÇİKA, 25 Mayıs 2020, ISSN: 2577-2465

AYGÜL MEHMET ALİ, NAZZAL MAHMOUD, EKTİ ALİ RIZA, GÖRÇİN ALİ, DA COSTA DANİEL BENEVİDES, ATEŞ HASAN FEHMİ, ARSLAN HÜSEYİN

Ali Görçin Tam metin bildiri

Deep learning frameworks to learn prediction and simulation focused control system models

Springer Science and Business Media LLC, Vol. 52, No. 1, Ocak 2022, ISSN: 0924-669X

TUNA TURCAN, BEKE AYKUT, KUMBASAR TUFAN

Tufan Kumbasar Özgün Makale Nonlinear system identification Time series prediction Deep learning Autoencoders LSTM

Derin Öğrenme Teknikleriyle ile Online Satış Tahminleri Yapılması: Fast Food Sektörü Uygulaması

19. Uluslararası Ekonometri, Yöneylem Araştırması ve İstatistik Sempozyumu, Antalya/TÜRKİYE, 17 Ekim 2018

SİVRİ MAHMUT SAMİ

Mahmut Sami Sivri Özet Bildiri Makine öğrenmesiZaman serisiTalep tahminiFast food sektörüLSTMKantil regresyonRassal ormanlarARIMA

Predicting Ocean Energy Harvesting Dynamics using LSTM Deep Learning Network

34th Asian-Pacific Technical Exchange and Advisory Meeting on Marine Structures TEAM 2020/21 Conference, İstanbul/TÜRKİYE, 6 Aralık 2021, s. 416-423

ALAN ALİ RIZA, BAYINDIR CİHAN

Cihan Bayındır Tam metin bildiri

Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning

MEDICAL IMAGE ANALYSIS, Vol. 55, No. null, Temmuz 2019, s. 136-147, ISSN: 1361-8415

ÖKSÜZ İLKAY,RUİJSİNK BRAM,PUYOL-ANTON ESTHER,CLOUGH JAMES R.,CRUZ GASTAO,BUSTİN AURELİEN,PRİETO CLAUDİA,BOTNAR RENE,RUECKERT DANİEL,SCHNABEL JULİA A.,KİNG ANDREW P.

İlkay Öksüz Özgün Makale Cardiac MR motion artefactsImage quality assessmentArtifactConvolutional neural networksLSTMNEURAL-NETWORKSQUALITY ASSESSMENT

CHARACTERIZATION AND MODELING OF NEGATIVE-BIAS TEMPERATURE INSTABILITY IN 40 NM CMOS TECHNOLOGY THROUGH LONG SHORT-TERM MEMORY (LSTM) NETWORKS

Fen Bilimleri Enstitüsü, İstanbul Teknik Üniversitesi, 2023

FİKRET BAŞAR GENCER

Mustafa Berke Yelten Tez Yüksek Lisans Devam Ediyor

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