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Deep Neural Networks For Named Entity Recognition On Social Media
(Fen Bilimleri Enstitüsü, 2018)
Named entity recognition (NER) on noisy data, specifically user-generated content (e.g. on-
line reviews, tweets) is a challenging task because of the presence of ill-formed text. In this
regard, while studies on ...
Boosting Video-Based Person Re-Identification With Synthetic Human Agents
(Fen Bilimleri Enstitüsü, 2019-09)
In recent years, research made in person re-identification has gained quite a bit of
significance due to the increasing demand from a broad range of application fields with
security and surveillance topping the list. A ...
An Rnn-Based Approach for Dıscoverıng Inconsıstencıes Between Permıssıons and Metadata In Androıd Applıcatıons
(Fen Bilimleri Enstitüsü, 2019-09)
Since mobile devices are increasingly on hand today, users have become more heavily involved with their use in accessing the Internet. Today, most mobile devices use the Android operating system. On mobile devices, users' ...
Neural Word Embeddings for Sentiment Analysis
(Fen Bilimleri Enstitüsü, 2020)
Most pre-trained word embeddings are achieved from context-based learning algorithms trained over a large text corpus. This leads to learning similar vectors for words that share most of their contexts, while expressing ...
Temporal Anomaly Localızatıon In Vıdeo
(Fen Bilimleri Enstitüsü, 2021-10-14)
Detecting anomalies in surveillance videos is an important research problem in computer vision. In this thesis, we propose two deep network architectures for anomaly detection, Anomaly Detection Network (ADNet) and Anomaly ...
Automatic Generation of Scientific Terminology with Deep Learning
(Fen Bilimleri Enstitüsü, 2021)
Automatic term extraction is an essential task in natural language processing. In this thesis, we work on terminology extraction for two purposes. The first aim is to measure inconsistency of scientific terminology for ...
Towards Understandıng Intuıtıve Physıcs Wıth Language And Vısıon
(Fen Bilimleri Enstitüsü, 2021)
Visual question answering (VQA) is one of the difficult tasks in multimodal machine reasoning. VQA requires machines to provide correct answers to questions about an image or a video. Here, the machine should perceive the ...
An Attention Based Deep Neural Network Architecture for Identification of Phishing URLS Through Character Level N-Gram Embeddings
(Fen Bilimleri Enstitüsü, 2022-06-24)
Despite the various technological advancements that have been made in the fight against phishing attacks, the problem still remains one of the most common threats in the cybersecurity domain. Due to the increasing number ...
Monocular Depth Estimation with Self-Supervised Representation Learning
(Fen Bilimleri Enstitüsü, 2022)
Many representation and modalities are developed for better scene understanding as images, videos, point clouds, etc. In this thesis, we intentionally characterize scene representation as depth maps in order to leverage ...
Real-Time Radar Tracking System With Deep Learning
(Fen Bilimleri Enstitüsü, 2023)
Real-time data tracking plays an essential role in the flight test processes of an aircraft. The data flowing from the aircraft to the ground control center must be real-time and uninterrupted. However, sometimes ground ...