Anlamsal Boşluk Doldurulmasında Derin Öğrenme Yöntemlerinin Kullanılması Üzerine Bir İnceleme

Yıl 2024, Cilt: 7 Sayı: 1, 54 - 62, 30.06.2024

İbrahim Ali Metin Bahadir Karasulu

Öz

Anlamsal boşluk kavramı, makineler aracılığıyla veriden elde edilen temel renk, doku ve şekil gibi özniteliklerle insan tarafından aynı veriye bakıldığında algı yoluyla tanımlanan kavramsal sonuçların farklılıklarından doğmaktadır. Bu boşluğun giderilmesi için çeşitli yol ve yöntemler literatürdeki çalışmalarda denenmiştir. Bu çalışmalarda, ontolojik sistemlerin geliştirildiği ve arama işlemlerinin de bu tarafa yoğunlaştırılmasının sağlandığı görülmektedir. Çalışmamızın ana amacı genel olarak Anlamsal Tabanlı Görüntüden Bilgi Elde Etme çalışmalarıyla İçerik Tabanlı Görüntüden Bilgi Elde Etme için gerçekleştirilen aramada ortaya çıkan Anlamsal Boşluk sorunun üstesinden gelinmesine dair yapılan çalışmaları ortaya koymaktır. Çalışmamızda literatürdeki çeşitli uluslararası dergi ve konferans yayınları incelenerek, kıyaslamalı özlü ve sistematik bir literatür taraması sunulmaktadır. Bilimsel tartışmaya da yer verilmektedir.

Anahtar Kelimeler

Yapay Zekâ, Görüntü İşleme, Anlamsal Boşluk, Derin Öğrenme, Evrişimli Sinir Ağı

A Review on Using Deep Learning Techniques to Bridge The Semantic Gap

Öz

The concept of semantic gap arises from the differences between the basic attributes such as color, texture and shape extracted from the data by machines and the conceptual results defined by human perception when looking at the same data. Various ways and methods have been tried in the literature to bridge this gap. In these studies, it is seen that ontological systems have been developed and search operations have been focused in this direction. The main purpose of our study is to present the studies on Semantic Based Image Retrieval in general and the studies on overcoming the Semantic Gap problem that arises in the search for Content Based Image Retrieval. We present a concise and systematic comparative literature review by analyzing various international journal and conference publications in the literature. Scientific discussion is also included.

Anahtar Kelimeler

Artificial Intelligence, Image Processing, Semantic Gap, Deep Learning, Convolutional Neural Network

Kaynakça

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