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Toplam kayıt 11, listelenen: 1-10
An adaptive locally connected neuron model: Focusing neuron
(Elsevier B.V., 2021-01-02)
This paper presents a new artificial neuron model capable of learning its receptive field in the topological domain of inputs. The experiments include tests of focusing neuron networks of one or two hidden layers on synthetic ...
Improved microphone array design with statistical speaker verification
(Elsevier Ltd, 2021-04)
Conventional microphone array implementations aim to lock onto a source with given location and if required, tracking it. It is a challenge to identify the intended source when the location of the source is unknown and ...
On the maximum cardinality cut problem in proper interval graphs and related graph classes
(Elsevier B.V., 2022-01-04)
Although it has been claimed in two different papers that the maximum cardinality cut problem is polynomial-time solvable for proper interval graphs, both of them turned out to be erroneous. In this work we consider the ...
Unsupervised textile defect detection using convolutional neural networks
(Elsevier Ltd, 2021-12)
In this study, we propose a novel motif-based approach for unsupervised textile anomaly detection that combines the benefits of traditional convolutional neural networks with those of an unsupervised learning paradigm. It ...
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 ...
A mobile app that uses neurofeedback and multi-sensory learning methods improves reading abilities in dyslexia: a pilot study
(Routledge, 2022-07-03)
Reading comprehension is difficult to improve for children with dyslexia because of the continuing demands of orthographic decoding in combination with limited working memory capacity. Children with dyslexia get special ...
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, ...
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 ...
ComStreamClust: a communicative multi-agent approach to text clustering in streaming data
(Springer Science and Business Media Deutschland GmbH, 2023-12)
Topic detection is the task of determining and tracking hot topics in social media. Twitter is arguably the most popular platform for people to share their ideas with others about different issues. One such prevalent issue ...
BinBRO: Binary Battle Royale Optimizer algorithm
(Elsevier Ltd, 2022-02-04)
Stochastic methods attempt to solve problems that cannot be solved by deterministic methods with reasonable time complexity. Optimization algorithms benefit from stochastic methods; however, they do not guarantee to obtain ...