ARAMA SONUÇLARI

Toplam 59 adet sonuçtan 20 tanesi görüntülenmektedir.

A deep learning approach to analyse ship inspection reports via natural language processing integrated with artificial neural network

Journal of Marine Engineering & Technology, Mayıs 2024, ISSN: 2046-4177

BİÇEN SAMET,ÇELİK METİN

Samet Biçen Özgün Makale Deep learning approach ship inspection natural language processing artificial neural network classifier marine root cause analysis tool

A deep learning approach to EEG based epilepsy seizure determination

2016 24th Signal Processing and Communication Application Conference (SIU), 16 Mayıs 2016

CILASUN HUSREV,YALÇIN HÜLYA

Hülya Yalçın Tam metin bildiri

Guided Soft Actor Critic: A Guided Deep Reinforcement Learning Approach for Partially Observable Markov Decision Processes

IEEE Access, Vol. 9, Aralık 2021, ISSN: 2169-3536

HAKLIDIR MEHMET, TEMELTAŞ HAKAN

Hakan Temeltaş Özgün Makale

Automatic Building Extraction using Kernel-based Deep Learning Approach from VHR Imagery

5th Intercontinental Geoinformation Days, NEW DELPHI/HİNDİSTAN, 14 Aralık 2022

BAKIRMAN TOLGA, SELBESOĞLU MAHMUT OĞUZ

Mahmut Oğuz Selbesoğlu Tam metin bildiri

Land cover and land use classification of multi-modal high-resolution satellite images using multi-task deep learning approach

Bilişim Enstitüsü, İstanbul Teknik Üniversitesi, 2021

BURAK EKİM

Elif Sertel Tez Yüksek Lisans Tamamlandı

Building detection from very high resolution satellite images with deep learning approach

Lisansüstü Eğitim Enstitüsü, İstanbul Teknik Üniversitesi, 2021

ESRA ÖZAYDIN

Elif Sertel Tez Yüksek Lisans Tamamlandı

Swarm fighter aircraft control with deep reinforcement learning approach

Lisansüstü Eğitim Enstitüsü, İstanbul Teknik Üniversitesi, 2025

METİN SARI

Fikret Çalışkan Tez Yüksek Lisans Tamamlandı

Hybrid deep learning approach for multiclass prediction offintech startups

Lisansüstü Eğitim Enstitüsü, İstanbul Teknik Üniversitesi, 2025

MORTEZA ROKHASHMAH

Cumhur Enis Ekinci Tez Yüksek Lisans Tamamlandı

NOISE REMOVAL OF THERMAL IMAGES USING DEEP LEARNING APPROACH

Fen Bilimleri Enstitüsü, İstanbul Teknik Üniversitesi, 2020

AHMET ÇAPCI

Behçet Uğur Töreyin Tez Yüksek Lisans Devam Ediyor

Data-Driven Approach for Estimating Power and Fuel Consumption of Ship: A Case of Container Vessel

Mathematics, Vol. 10, No. 22, Kasım 2022, ISSN: 2227-7390

UYANIK TAYFUN, YALMAN YUNUS, KALENDERLİ ÖZCAN, ARSLANOĞLU YASİN, TERRİCHE YACİNE TERRİCHE, SU CHUN-LİEN, GUERRERO JOSEP M.

Yasin Arslanoğlu Özgün Makale fuel consumption; energy efficiency; machine learning; deep neural network; power prediction

A Data-Driven Multi-Regime Approach for Predicting Energy Consumption

ENERGIES, Vol. 14, No. 20, Ekim 2021, ISSN: 1996-1073

KAHRAMAN ABDULGANI, KANTARDZIC MEHMED, KAHRAMAN MUHAMMET MUSTAFA, KOTAN MUHAMMED

Muhammet Mustafa Kahraman Özgün Makale energy efficiency; energy consumption prediction; concept drift; deep learning; industrial machines

A direct learning approach for detection of hotspots in microwave hyperthermia treatments

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, Vol. 63, No. 8, Ocak 2025, s. 12, ISSN: 0140-0118

ÖNAL HULUSİ,GİRGİN ENES,DOĞU SEMİH,YILMAZ ABDOLSAHEB TUBA,AKINCI MEHMET NURİ

Tuba Yılmaz Abdolsaheb Özgün Makale Breast imaging Deep learning Hyperthermia Microwave imaging Temperature monitoring

A direct learning approach for detection of hotspots in microwave hyperthermia treatments

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, Vol. 63, No. 8, Ocak 2025, s. 12, ISSN: 0140-0118

ÖNAL HULUSİ,GİRGİN ENES,DOĞU SEMİH,YILMAZ ABDOLSAHEB TUBA,AKINCI MEHMET NURİ,GİRGİN ENES

Mehmet Nuri Akıncı Özgün Makale Breast imaging Deep learning Hyperthermia Microwave imaging Temperature monitoring

MACHINE VISION BOBBIN ANALYSIS SYSTEM WITH DEEP LEARNING APPROACH

3rd International Congress of Innovative Textiles (ICONTEX 2022), 18 Mayıs 2022

EMEKDAR ELÇİN, AÇIKGÖZ TUFAN HATİCE, ŞAHİN UMUT KIVANÇ, KURŞUN BAHADIR SENEM, AYATA KONUKOĞLU SEVAL, CANSU BATÇIK, BAYTAN T.K., ÇATAK E., ŞENTÜRK Ç.D.

Senem Kurşun Tam metin bildiri

Innovative deep learning approach for cross-crop plant disease detection: A generalized method for identifying unhealthy leaves

INFORMATION PROCESSING IN AGRICULTURE, Vol. 12, No. 1, Ocak 2025, s. 14, ISSN: 2214-3173

FAROU BRAHİM,SERİDİ HAMİD,BOUACİDA IMANE,DJAKHDJAKHA LYNDA,KURULAY MUHAMMED

Muhammed Kurulay Özgün Makale Deep learning Agriculture Plant diseases Image processing Disease detection Leaf splitting

MONITORING OF GLACIERS ON HORSESHOE ISLAND, ANTARCTICA BASED ON A DEEP LEARNING APPROACH FROM HIGH-RESOLUTION ORTHOPHOTOS (TAE-6 & TAE-7)

GeoAdvances 2024 – 8th International Conference on GeoInformation Advances,, İstanbul/TÜRKİYE, 11 Ocak 2024

SELBESOĞLU MAHMUT OĞUZ,BAKIRMAN TOLGA,KARABULUT MUSTAFA FAHRİ,GÜNAYDIN ESRA,VASSİLEV OLEG,OKTAR ÖZGÜN,ÖZSOY BURCU

Mahmut Oğuz Selbesoğlu Tam metin bildiri

A New Approach for Tactical Decision Making in Lane Changing: Sample Efficient Deep Q Learning with a Safety Feedback Reward

IEEE Intelligent Vehicles Symposium, 19 Eylül 2020

YAVAŞ MUHARREM UĞUR,KUMBASAR TUFAN,ÜRE NAZIM KEMAL

Tufan Kumbasar Tam metin bildiri

Integration of Optical Coherence Tomography Images and Real-Life Clinical Data for Deep Learning Modeling: A Unified Approach in Prognostication of Diabetic Macular Edema

JOURNAL OF BIOPHOTONICS, Vol. 8, No. 3, Mart 2025, s. 1-8, ISSN: 1864-063X

ATİK MUHAMMED ENES,KOÇAK İBRAHİM,SAYIN NİHAT,BAYRAMOĞLU SADIK ETKA,ÖZYİĞİT AHMET

Muhammed Enes Atik Özgün Makale clinical data deep learning diabetic macular edema diabetic retinopathy OCT images

Detecting Multiclass Objects in Remote Sensing Imagery: A Deep Learning Approach

4th International Conference on Computer, Remote Sensing and Aerospace, 5 Temmuz 2024

BÜYÜKKANBER FURKAN,YANALAK MUSTAFA,MUSAOĞLU NEBİYE

Mustafa Yanalak Tam metin bildiri

Climate model-driven seasonal forecasting approach with deep learning

Environmental Data Science, Vol. 2, Ocak 2023, ISSN: 2634-4602

ÜNAL ALPER,ASAN BUSRA,SEZEN İSMAİL,YESİLKAYNAK BUGRA,AYDIN YUSUF,ILICAK MEHMET,ÜNAL GÖZDE

Yusuf Aydın Özgün Makale climate change deep neural networksmachine learningseasonal forecast

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