Browsing Faculty of Engineering by Title
Now showing items 486-505 of 3117
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Deep learning-based blind image super-resolution with iterative kernel reconstruction and noise estimation
(Elsevier, 2023-08)Blind single image super-resolution (SISR) is a challenging task in image processing due to the ill-posed nature of the inverse problem. Complex degradations present in real life images make it difficult to solve this ... -
Deep learning-based expressive speech synthesis: a systematic review of approaches, challenges, and resources
(Springer, 2024-02-12)Speech synthesis has made significant strides thanks to the transition from machine learning to deep learning models. Contemporary text-to-speech (TTS) models possess the capability to generate speech of exceptionally high ... -
Deep learning-based speaker-adaptive postfiltering with limited adaptation data for embedded text-to-speech synthesis systems
(Elsevier, 2023-06)End-to-end (e2e) speech synthesis systems have become popular with the recent introduction of text-to-spectrogram conversion systems, such as Tacotron, that use encoder–decoder-based neural architectures. Even though those ... -
Deep multi-object symbol learning with self-attention based predictors
(IEEE, 2023)This paper proposes an architecture that can learn symbolic representations from the continuous sensorimotor experience of a robot interacting with a varying number of objects. Unlike previous works, this work aims to ... -
Deep Q-learning based optimization of VLC systems with dynamic time-division multiplexing
(IEEE, 2020)The traditional method to solve nondeterministic-polynomial-time (NP)-hard optimization problems is to apply meta-heuristic algorithms. In contrast, Deep Q Learning (DQL) uses memory of experience and deep neural network ... -
Deep reinforcement based power allocation for the max-min optimization in non-orthogonal multiple access
(IEEE, 2020)NOMA is a radio access technique that multiplexes several users over the frequency resource and provides high throughput and fairness among different users. The maximization of the minimum the data-rate, also known as ... -
Deep reinforcement learning approach for trading automation in the stock market
(IEEE, 2022)Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining the financial assets price 'prediction' ... -
Deep reinforcement learning for acceptance strategy in bilateral negotiations
(TÜBİTAK, 2020)This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance ... -
Deepsym: Deep symbol generation and rule learning for planning from unsupervised robot interaction
(AI Access Foundation, 2022)Symbolic planning and reasoning are powerful tools for robots tackling complex tasks. However, the need to manually design the symbols restrict their applicability, especially for robots that are expected to act in open-ended ... -
Defect-aware nanocrossbar logic mapping through matrix canonization using two-dimensional radix sort
(ACM, 2011-08)Nanocrossbars (i.e., nanowire crossbars) offer extreme logic densities but come with very high defect rates; stuck-open/closed, broken nanowires. Achieving reasonable yield and utilization requires logic mapping that is ... -
Defining architectural viewpoints for quality concerns
(Springer Science+Business Media, 2011)A common practice in software architecture design is to apply architectural views to model the design decisions for the various stakeholder concerns. When dealing with quality concerns, however, it is more difficult to ... -
Delegation vs. control of component procurement under asymmetric cost information and simple contracts
(Informs, 2013)A manufacturer must choose whether to delegate component procurement to her tier 1 supplier or control it directly. Because of information asymmetry about suppliers’ production costs and the use of simple quantity discount ... -
Delivery phase in cache-based wireless networks with modified LT codes
(Springer Nature, 2020-10)Caching has emerged as an efficient technique to reduce delivery latency and network congestion. The focus of this paper is on content delivery in the caching-based wireless systems. In view of the fact that in such systems, ... -
Demand-driven electricity supply options of electric vehicles: modelling, simulation, and management strategy of public charging stations
(Springer, 2021-10-13)In this chapter, we discuss the challenges and research opportunities in the demand-driven electricity supply options of electric vehicles (EVs) at public charging stations (CSs). EVs have gained increased attention in ... -
Democratization of HPC cloud services with automated parallel solvers and application containers
(Wiley, 2018-11-10)In this paper, we investigate several design choices for HPC services at different layers of the cloud computing architecture to simplify and broaden its use cases. We start with the platform-as-a-service (PaaS) layer and ... -
Democratization of runtime verification for internet of things
(Elsevier, 2018-05)Internet of Things (IoT) devices have gained more prevalence in ambient assisted living (AAL) systems. Reliability of AAL systems is critical especially in assuring the safety and well-being of elderly people. Runtime ... -
Deniz: A robust bidding strategy for negotiation support systems
(Springer, 2021)This paper presents the Deniz agent that has been specifically designed to support human negotiators in their bidding. The design of Deniz is done with the criteria of robustness and the availability of small data, due to ... -
Dependence of inclusive jet production on the anti-kT distance parameter in pp collisions at s√ = 13 TeV
(Springer Nature, 2020-12-11)The dependence of inclusive jet production in proton-proton collisions with a center-of-mass energy of 13 TeV on the distance parameter R of the anti-k(T) algorithm is studied using data corresponding to integrated ... -
Dependent absorption and scattering by interacting nanoparticles
(Begell House Inc., 2010)Dependent light scattering and absorption patterns of metallic nano-sized particles in interaction with other spherical and cone-like structures were investigated. The numerical solution of the light scattering problem was ... -
Depression screening from voice samples of patients affected by parkinson’s disease
(S. Karger AG, 2019-05-01)Depression is a common mental health problem leading to significant disability worldwide. It is not only common but also commonly co-occurs with other mental and neurological illnesses. Parkinson's disease (PD) gives rise ...
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