Konu "Deep learning" için listeleme
Toplam kayıt 25, listelenen: 1-20
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Adaptive convolution kernel for artificial neural networks
(Academic Press Inc., 2021-02)Many deep neural networks are built by using stacked convolutional layers of fixed and single size (often 3 × 3) kernels. This paper describes a method for learning the size of convolutional kernels to provide varying size ... -
Analysis of single image super resolution models
(IEEE, 2022-11-18)Image Super-Resolution (SR) is a set of image processing techniques which improve the resolution of images and videos. Deep learning approaches have made remarkable improvement in image super-resolution in recent years. ... -
Animal sound classification using a convolutional neural network
(IEEE, 2018-12-06)In this paper, we investigate the problem of animal sound classification using deep learning and propose a system based on convolutional neural network architecture. As the input to the network, sound files were preprocessed ... -
Application of ChatGPT in the tourism domain: potential structures and challenges
(IEEE, 2023-12-23)The tourism industry stands out as a sector where effective customer communication significantly influences sales and customer satisfaction. The recent shift from traditional natural language processing methodologies to ... -
Automatic propbank generation for Turkish
(Incoma Ltd, 2019-09)Semantic role labeling (SRL) is an important task for understanding natural languages, where the objective is to analyse propositions expressed by the verb and to identify each word that bears a semantic role. It provides ... -
BOUN-ISIK participation: an unsupervised approach for the named entity normalization and relation extraction of Bacteria Biotopes
(Association for Computational Linguistics (ACL), 2019-11-04)This paper presents our participation at the Bacteria Biotope Task of the BioNLP Shared Task 2019. Our participation includes two systems for the two subtasks of the Bacteria Biotope Task: the normalization of entities ... -
Closeness and uncertainty aware adversarial examples detection in adversarial machine learning
(Elsevier Ltd, 2022-07)While deep learning models are thought to be resistant to random perturbations, it has been demonstrated that these architectures are vulnerable to deliberately crafted perturbations, albeit being quasi-imperceptible. These ... -
CNN-Based deep learning architecture for electromagnetic imaging of rough surface profiles
(IEEE, 2022-10)A convolutional neural network (CNN) based deep learning (DL) technique for electromagnetic imaging of rough surfaces separating two dielectric media is presented. The direct scattering problem is formulated through the ... -
Convolutional attention network for MRI-based Alzheimer's disease classification and its interpretability analysis
(IEEE, 2021-09-17)Neuroimaging techniques, such as Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET), help to identify Alzheimer's disease (AD). These techniques generate large-scale, high-dimensional, multimodal ... -
Convolutional neural network (CNN) algorithm based facial emotion recognition (FER) system for FER-2013 dataset
(IEEE, 2022-11-18)Facial expression recognition (FER) is the key to understanding human emotions and feelings. It is an active area of research since human thoughts can be collected, processed, and used in customer satisfaction, politics, ... -
Deep learning techniques for building density estimation from remotely sensed imagery
(Işık Üniversitesi, 2019-04-05)This thesis is about point-wise estimation of building density on the remote sensing optical imageries by applying deep learning methods. The goal of the project is to reduce mean square error of the estimated density by ... -
Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images
(Elsevier B.V., 2021-06)The novel coronavirus (COVID-19) could be described as the greatest human challenge of the 21st century. The development and transmission of the disease have increased mortality in all countries. Therefore, a rapid diagnosis ... -
El yazısı rakam sınıflandırması için gözetimsiz benzerlik tabanlı evrişimler
(Institute of Electrical and Electronics Engineers Inc., 2022)Effective training of filters in Convolutional Neural Networks (CNN) ensures their success. In order to achieve good classification results in CNNs, filters must be carefully initialized, trained and fine-tuned. We propose ... -
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples
(Springer, 2022-03)Deep neural network (DNN) architectures are considered to be robust to random perturbations. Nevertheless, it was shown that they could be severely vulnerable to slight but carefully crafted perturbations of the input, ... -
Malaria parasite detection with deep transfer learning
(IEEE, 2018-12-06)This study aims to automatically detect malaria parasites (Plasmodium sp) on images taken from Giemsa stained blood smears. Deep learning methods provide limited performance when sample size is low. In transfer learning, ... -
Multi-task learning on mental disorder detection, sentiment detection and emotion detection
(Işık Üniversitesi, 2024-02-12)Suicidal behavior is a global cause of life-threatening injury and most of the time, death. Mental disorders such as depression, anxiety, and bipolar are prevalent among the youth in recent decades. Social media are popular ... -
An open, extendible, and fast Turkish morphological analyzer
(Incoma Ltd, 2019-09)In this paper, we present a two-level morphological analyzer for Turkish which consists of five main components: finite state transducer, rule engine for suffixation, lexicon, trie data structure, and LRU cache. We use ... -
Predicting the ocean currents using deep learning
(Işık University Press, 2023-01)In this paper, we analyze the predictability of the ocean currents using deep learning. More specifically, we apply the Long Short Term Memory (LSTM) deep learning network to a data set collected by the National Oceanic ... -
Recovery of impenetrable rough surface profiles via CNN-based deep learning architecture
(Taylor and Francis Ltd., 2022-08-18)In this paper, a convolutional neural network (CNN)-based deep learning (DL) architecture for the solution of an electromagnetic inverse problem related to imaging of the shape of the perfectly electric conducting (PEC) ... -
Supervised decision making in forex investment using ML and DL classification methods
(Işık Üniversitesi, 2023-07-20)The suggested trading system offers an approach that takes into account the complexity and high trading volume of the foreign exchange (FX0) market. Its main objective is to address the challenges faced by traders in the ...