Suchergebnisse - "Computer Learning and Pattern Recognition::Other"

Augmenting Clip-based few shot recognition using shapes and concepts ; Şekiller ve kavramlar kullanarak Clip tabanlı az örnekli tanımayı geliştirme

Autoren: Güder, Erce Akbaş, Emre Department of Computer Engineering

Weitere Verfasser: Güder, Erce Akbaş, Emre Department of Computer Engineering

Schlagwörter: object recognition, image classification, few-shot learning, CLIP adaptation, deep learning, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Neural Networks, Computer Learning and Pattern Recognition::Pattern Recognition and Image Processing, Computer Learning and Pattern Recognition::Other

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/115645

Verfügbarkeit: https://hdl.handle.net/11511/115645

Task Assignment and Path Planning for Capacitated Agents Engaged in Lifelong Pickup and Delivery Tasks ; Yaşam Boyu Alma ve Teslimat Görevleri Yapan Kapasiteli Etmenler İçin Görev Atama ve Yol Planlama

Autoren: Çilden, Evren Polat, Faruk Department of Computer Engineering

Weitere Verfasser: Çilden, Evren Polat, Faruk Department of Computer Engineering

Schlagwörter: Multi-Agent Path Finding, Multi-Agent Pickup and Delivery, Heuristic Search, Task Assignment, Arbis Subjects::Engineering and Technology, Arbis Subjects::Engineering and Technology::Computer Sciences, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition, Computer Learning and Pattern Recognition::Other

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/115547

Verfügbarkeit: https://hdl.handle.net/11511/115547

A comparative study of prompting and fine-tuning for binary text classification of sustainable development goals ; Sürdürülebilir kalkınma amaçlarının ikili metin sınıflandırmasında istemleme ve ince-ayar üzerine karşılaştırmalı bir çalışma

Autoren: Atay, Mert Angın, Pelin Department of Computer Engineering

Weitere Verfasser: Atay, Mert Angın, Pelin Department of Computer Engineering

Schlagwörter: Large language models, Fine-tuning, Prompting, Prompt engineering, Binary text classification, Sustainable development goals, Natural language processing, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Natural Language Processing, Computer Learning and Pattern Recognition::Computer Learning, Computer Learning and Pattern Recognition::Neural Networks, Computer Learning and Pattern Recognition::Other, Arbis Subjects::Engineering and Technology::Computer Sciences

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/111537

Verfügbarkeit: https://hdl.handle.net/11511/111537

Forecasting wind power generation with ensembling techniques ; Topluluk yaklaşimlariyla rüzgar enerjisi üretimi tahmini

Autoren: Özertaş, Yunus Emre Gökalp Yavuz, Fulya Department of Statistics

Weitere Verfasser: Özertaş, Yunus Emre Gökalp Yavuz, Fulya Department of Statistics

Schlagwörter: Ensemble architecture, Machine learning, Statistical learning, Time series, Wind power forecasting, Arbis Subjects::Natural Sciences::Statistics::Statistical Analysis and Applications, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Other, Arbis Subjects::Natural Sciences::Statistics

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/111443

Verfügbarkeit: https://hdl.handle.net/11511/111443

Developing novel methods on data stream classification and clustering for accuracy improvement ; Veri akışı sınıflandırma ve kümeleme üzerine doğruluğu artırmaya yönelik yeni yöntemler geliştirilmesi

Autoren: Maden, Engin Karagöz, Pınar Department of Computer Engineering

Weitere Verfasser: Maden, Engin Karagöz, Pınar Department of Computer Engineering

Schlagwörter: Data stream classification, Sliding window, Hybrid classifier, Short text stream clustering, Word relation network, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Computer Learning, Computer Learning and Pattern Recognition::Other

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/111446

Verfügbarkeit: https://hdl.handle.net/11511/111446

Effective reinforcement learning through intrinsic motivation and visual external memory in partially observable environments ; Kısmi gözlemlenebilir ortamlarda içsel motivasyon ve görsel harici bellek ile etkili pekiştirmeli öğrenme

Autoren: Demirbilek, Burak Han Polat, Faruk Demir, Alper et al.

Weitere Verfasser: Demirbilek, Burak Han Polat, Faruk Demir, Alper et al.

Schlagwörter: Reinforcement learning, Partial observability, External memory management, Intrinsic motivation, Arbis Subjects::Engineering and Technology::Computer Sciences, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition, Computer Learning and Pattern Recognition::Neural Networks, Computer Learning and Pattern Recognition::Other, Computer Learning and Pattern Recognition::Computer Learning, Arbis Subjects::Engineering and Technology::Computer Sciences::Algorithms::Simulation and Modelling

Dateibeschreibung: 106 pages; application/pdf

Relation: https://hdl.handle.net/11511/105568

Verfügbarkeit: https://hdl.handle.net/11511/105568

A COMPARATIVE STUDY OF DEEP LEARNING TECHNIQUES FOR TIME SERIES FORECASTING IN ENERGY CONSUMPTION PREDICTION ; DERİN ÖĞRENME TEKNİKLERİ İLE ENERJİ TÜKETİMİNİ TAHMİN ETMEK İÇİN ZAMAN SERİSİ TAHMİNİNE YÖNELİK KARŞILAŞTIRMALI BİR ÇALIŞMA

Autoren: Tayib, Mutakabbir Ahmed Taşkaya Temizel, Tuğba Yozgatlıgil, Ceylan et al.

Weitere Verfasser: Tayib, Mutakabbir Ahmed Taşkaya Temizel, Tuğba Yozgatlıgil, Ceylan et al.

Schlagwörter: Time Series Forecasting, Deep Learning Models, Attention-based Transformers, Research Transparency, Green AI, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Other, Arbis Subjects::Engineering and Technology::Information Systems, Communication and Control Engineering::Other

Dateibeschreibung: 169 pages; application/pdf

Relation: https://hdl.handle.net/11511/104845

Verfügbarkeit: https://hdl.handle.net/11511/104845

Fast EEG based biometrics via mean curve length ; Ortalama eğri uzunluğu kullanılarak gerçekleştirilen hızlı EEG tabanlı biyometri

Autoren: Yahyaei, Reza Özkurt, Tolga Esat Department of Medical Informatics

Weitere Verfasser: Yahyaei, Reza Özkurt, Tolga Esat Department of Medical Informatics

Schlagwörter: Mean Curve Length, Fractal Dimension, EEG, Biometrics, Mahalanobis Classifier, Arbis Subjects::Engineering and Technology::Biomedical Engineering::Biosignal Processing, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Other, Arbis Subjects::Health Sciences

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/96714

Verfügbarkeit: https://hdl.handle.net/11511/96714

EXTRACTING EXPLICIT RELATIONAL INFORMATION FROM A NEW RELATIONAL REASONING TESTBED WITH A LEARNING AGENT ; YENİ BİR İLİŞKİSEL AKIL YÜRÜTME TEST ORTAMINDAN BELİRGİN İLİŞKİSEL BİLGİLERİ BİR ÖĞRENME AJANI İLE ÇIKARMAK

Autoren: Küçüksubaşı, Faruk Sürer, Elif Department of Modeling and Simulation

Weitere Verfasser: Küçüksubaşı, Faruk Sürer, Elif Department of Modeling and Simulation

Schlagwörter: relational reinforcement learning, relational reasoning, relation networks, attention networks, reinforcement learning, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Other

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/91658

Verfügbarkeit: https://hdl.handle.net/11511/91658

DEEP LEARNING-BASED UNROLLED RECONSTRUCTION METHODS FOR COMPUTATIONAL IMAGING ; HESAPLAMALI GÖRÜNTÜLEME İÇİN DERİN ÖĞRENME TABANLI GERİÇATIM YÖNTEMLERİ

Autoren: Bezek, Can Deniz Öktem, Sevinç Figen Department of Electrical and Electronics Engineering

Weitere Verfasser: Bezek, Can Deniz Öktem, Sevinç Figen Department of Electrical and Electronics Engineering

Schlagwörter: computational imaging, spectral imaging, inverse problems, image reconstruction, deep learning, algorithm unrolling, truncated convolution, Arbis Subjects::Engineering and Technology::Electrical and Electronics Engineering::Other, Arbis Subjects::Engineering and Technology::Computer Sciences::Artificial Intelligence, Computer Learning and Pattern Recognition::Other, Arbis Subjects::Engineering and Technology::Information Systems, Communication and Control Engineering::Signal Processing::Image and Video Processing

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/11511/93159

Verfügbarkeit: https://hdl.handle.net/11511/93159