A novel fuzzy similarity measure and prevalence estimation approach for similarity profiled temporal association pattern mining
Abstract Data generated from Sensors, IoT environment and many real time applications is
mainly spatial, temporal, or spatio-temporal. Some of them include data generated from …
mainly spatial, temporal, or spatio-temporal. Some of them include data generated from …
Embedded vision systems: A review of the literature
Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA)
for the acceleration of various vision systems mainly on embedded devices have become …
for the acceleration of various vision systems mainly on embedded devices have become …
Supervised learning in spiking neural networks with noise-threshold
With a similar capability of processing spikes as biological neural systems, networks of
spiking neurons are expected to achieve a performance similar to that of living brains …
spiking neurons are expected to achieve a performance similar to that of living brains …
Bio-inspired approach to multistage image processing
LI Timchenko, SV Pavlov… - … , Industry, and High …, 2017 - spiedigitallibrary.org
Multistage integration of visual information in the brain allows people to respond quickly to
most significant stimuli while preserving the ability to recognize small details in the image …
most significant stimuli while preserving the ability to recognize small details in the image …
Image interpolation based on spiking neural network model
MO İncetaş - Applied Sciences, 2023 - mdpi.com
Image interpolation is used in many areas of image processing. It is seen that many
techniques developed to date have been successful in both protecting edges and increasing …
techniques developed to date have been successful in both protecting edges and increasing …
Image interpolation with spiking neural network based pixel similarity
M Kılıçaslan - Signal, Image and Video Processing, 2024 - Springer
Image interpolation is an important topic in the field of image processing. It is defined as the
process of transforming low-resolution images into high-resolution ones using image …
process of transforming low-resolution images into high-resolution ones using image …
Efficient training of supervised spiking neural networks via the normalized perceptron based learning rule
The spiking neural networks (SNNs) are the third generation of artificial neural networks,
which have made great achievements in the field of pattern recognition. However, the …
which have made great achievements in the field of pattern recognition. However, the …
Bioinspired approach to modeling retinal ganglion cells using system identification techniques
The processing capabilities of biological vision systems are still vastly superior to artificial
vision, even though this has been an active area of research for over half a century. Current …
vision, even though this has been an active area of research for over half a century. Current …
Kinetic model of vibration screening for granular materials based on biological neural network
Z Zhao, Y Zhang, F Qin, M ** - Particuology, 2024 - Elsevier
The kinetic model is the theoretical basis for optimizing the structure and operation
performance of vibration screening devices. In this paper, a biological neurodynamic …
performance of vibration screening devices. In this paper, a biological neurodynamic …
Anisotropic diffusion filter based on spiking neural network model
MO İncetaş - Arabian Journal for Science and Engineering, 2022 - Springer
Image denoising is one of the most important steps in image processing. Anisotropic
diffusion filters (ADFs), which are quite popular, stand out with their edge preservation …
diffusion filters (ADFs), which are quite popular, stand out with their edge preservation …