Browsing by Author "Kıraç, Mustafa Furkan"
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Adapting bilateral networks to monocular depth estimation for real-time inference
Monocular Depth Estimation (MDE) is a fundamental computer vision application area for many industry-related advances. Due to its deployment needs, the inference time of the depth estimation algorithm also plays a crucial ... -
ADVISOR: An adjustable framework for test oracle automation of visual output systems
Genç, A. E.; Sözer, Hasan; Kıraç, Mustafa Furkan; Aktemur, Tankut Barış (IEEE, 2020-09)Test oracles differentiate between the correct and incorrect system behavior. Automation of test oracles for visual output systems mainly involves image comparison, where a snapshot of the output is compared with respect ... -
AIM 2022 challenge on instagram filter removal: Methods and results
Kınlı, Osman Furkan; Menteş, Sami; Özcan, Barış; Kıraç, Mustafa Furkan (Springer, 2023)This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations, and the feature maps of the original ... -
Alt kesit seviyeleri arasında oy çoğunluğu ile sahne tanıma
In this paper, scene recognition problem, which is a frequently-studied field of computer vision, is tackled. Proposed algorithm utilizes bag of words (BoW) method along with considering sub-segments in the image during ... -
Automated maintenance support for data-tier software
Data-tier software includes the data model and business logic of enterprise systems, and it is subject to long-term maintenance. Even though the user interface of these systems can be completely replaced, data-tier software ... -
Automatically learning usage behavior and generating event sequences for black-box testing of reactive systems
Kıraç, Mustafa Furkan; Aktemur, Tankut Barış; Sözer, Hasan; Gebizli, C. Ş. (The ACM Digital Library, 2019-06)We propose a novel technique based on recurrent artificial neural networks to generate test cases for black-box testing of reactive systems. We combine functional testing inputs that are automatically generated from a model ... -
Autotuning runtime specialization for sparse matrix-vector multiplication
Yılmaz, Buse; Aktemur, Tankut Barış; Garzaran, M. J.; Kamin, S.; Kıraç, Mustafa Furkan (ACM, 2016-04)Runtime specialization is used for optimizing programs based on partial information available only at runtime. In this paper we apply autotuning on runtime specialization of Sparse Matrix-Vector Multiplication to predict ... -
A benchmark for inpainting of clothing images with irregular holes
Kınlı, Osman Furkan; Özcan, Barış; Kıraç, Mustafa Furkan (Springer, 2020)Fashion image understanding is an active research field with a large number of practical applications for the industry. Despite its practical impacts on intelligent fashion analysis systems, clothing image inpainting has ... -
Clothing image retrieval with triplet capsule networks
Kınlı, Osman Furkan (2019-08-19)Clothing image retrieval has become more important after some major developments in Computer Science and the emergence of e-commerce. Recent studies generally attack this problem by using Convolutional Neural Networks ... -
Description-aware fashion image inpainting with convolutional neural networks in coarse-to-fine manner
Kınlı, Osman Furkan; Özcan, Barış; Kıraç, Mustafa Furkan (The ACM Digital Library, 2020-04-14)Inpainting a particular missing region in an image is a challenging vision task, and promising improvements on this task have been achieved with the help of the recent developments in vision-related deep learning studies. ... -
Deterministic neural illumination mapping for efficient auto-white balance correction
Kınlı, Osman Furkan; Yılmaz, Doğa; Özcan, Barış; Kıraç, Mustafa Furkan (IEEE, 2023)Auto-white balance (AWB) correction is a critical operation in image signal processors for accurate and consistent color correction across various illumination scenarios. This paper presents a novel and efficient AWB ... -
An ecologically valid reference frame for perspective invariant action recognition
In robotics, objects and body parts can be represented in various coordinate frames to ease computation. In biological systems, body or body part centered coordinate frames have been proposed as possible reference frames ... -
Fashion image retrieval with capsule networks
Kınlı, Osman Furkan; Özcan, Barış; Kıraç, Mustafa Furkan (IEEE, 2019)In this study, we investigate in-shop clothing retrieval performance of densely-connected Capsule Networks with dynamic routing. To achieve this, we propose Triplet-based design of Capsule Network architecture with two ... -
Generalization to unseen viewpoint images of objects via alleviated pose attentive capsule agreement
Özcan, Barış; Kınlı, Osman Furkan; Kıraç, Mustafa Furkan (Springer, 2023-02)Despite their achievements in object recognition, Convolutional Neural Networks (CNNs) particularly fail to generalize to unseen viewpoints of a learned object even with substantial samples. On the other hand, recently ... -
Hierarchically constrained 3D hand pose estimation using regression forests from single frame depth data
Kıraç, Mustafa Furkan; Kara, Y. E.; Akarun, L. (Elsevier, 2014-12-01)The emergence of inexpensive 2.5D depth cameras has enabled the extraction of the articulated human body pose. However, human hand skeleton extraction still stays as a challenging problem since the hand contains as many ... -
Illumination-guided inverse rendering benchmark: Learning real objects with few cameras
Yılmaz, Doğa; Kıraç, Mustafa Furkan (Elsevier, 2023-10)The realm of 3D computer vision and graphics has experienced exponential growth recently, enabling the creation of realistic virtual environments and digital representations of real-world objects. Central to this progression ... -
Image denoising using deep convolutional autoencoder with feature pyramids
Çetinkaya, Ekrem; Kıraç, Mustafa Furkan (TÜBİTAK, 2020)Image denoising is 1 of the fundamental problems in the image processing field since it is the preliminary step for many computer vision applications. Various approaches have been used for image denoising throughout the ... -
Image denoising using deep convolutional autoencoders
Çetinkaya, Ekrem (2019-08-19)Image denoising is one of the fundamental problems in image processing eld since it is required by many computer vision applications. Various approaches have been used in image denoising throughout the years from spatial ... -
Improving regression performance on monocular 3D object detection using bin-mixing and sparse voxel data
Balatkan, Eren; Kıraç, Mustafa Furkan (IEEE, 2021)Accurate and fast 3D object detection plays a role of paramount importance for safe and capable autonomous machines. LiDAR point cloud based methods have demonstrated impressive results, yet expensive LiDAR sensors make ... -
Increasing visual detail for tv watchers with color vision deficiencies by using image processing methods
Kırgız, Gamze (2018-05)There are three types of cone cells in the human retina that respond to different color spectrums. The signals generated by these cone cells are combined and the color information is interpreted. Color blindness, or color ...
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