Search Results - "Smagulova, Kamilya"

Hardware implementation of memristor-based artificial neural networks by Aguirre, Fernando, Sebastian, Abu, Le Gallo, Manuel, Song, Wenhao, Wang, Tong, Yang, J. Joshua, Lu, Wei, Chang, Meng-Fan, Ielmini, Daniele, Yang, Yuchao, Mehonic, Adnan, Kenyon, Anthony, Villena, Marco A., Roldán, Juan B., Wu, Yuting, Hsu, Hung-Hsi, Raghavan, Nagarajan, Suñé, Jordi, Miranda, Enrique, Eltawil, Ahmed, Setti, Gianluca, Smagulova, Kamilya, Salama, Khaled N., Krestinskaya, Olga, Yan, Xiaobing, Ang, Kah-Wee, Jain, Samarth, Li, Sifan, Alharbi, Osamah, Pazos, Sebastian, Lanza, Mario

“…Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing…”
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Generalised Analog LSTMs Recurrent Modules for Neural Computing by Adam, Kazybek, Smagulova, Kamilya, James, Alex

“…The human brain can be considered as a complex dynamic and recurrent neural network. There are several models for neural networks of the human brain, that…”
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Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions by Smagulova, Kamilya, Fouda, Mohammed E., Eltawil, Ahmed

“…The high speed, scalability, and parallelism offered by ReRAM crossbar arrays foster the development of ReRAM-based next-generation AI accelerators. At the…”
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A survey on LSTM memristive neural network architectures and applications by Smagulova, Kamilya, James, Alex Pappachen

“…The recurrent neural networks (RNN) found to be an effective tool for approximating dynamic systems dealing with time and order dependent data such as video,…”
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A memristor-based long short term memory circuit by Smagulova, Kamilya, Krestinskaya, Olga, James, Alex Pappachen

“…Long-short term memory (LSTM) is a cognitive architecture that aims to mimic the sequence temporal memory processes in human brain. The state and…”
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Who is the Winner? Memristive-CMOS Hybrid Modules: CNN-LSTM Versus HTM by Smagulova, Kamilya, Krestinskaya, Olga, James, Alex

“…Hierarchical, modular and sparse information processing are signature characteristics of biological neural networks. These aspects have been the backbone of…”
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Resistive Neural Hardware Accelerators by Smagulova, Kamilya, Fouda, Mohammed E., Kurdahi, Fadi, Salama, Khaled N., Eltawil, Ahmed

“…Deep neural networks (DNNs), as a subset of machine learning (ML) techniques, entail that real-world data can be learned, and decisions can be made in real…”
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Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions by Smagulova, Kamilya, Fouda, Mohammed E, Eltawil, Ahmed

“…The higher speed, scalability and parallelism offered by ReRAM crossbar arrays foster development of ReRAM-based next generation AI accelerators. At the same…”
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Memristive LSTM network hardware architecture for time-series predictive modeling problems by Adam, Kazybek, Smagulova, Kamilya, James, Alex Pappachen

“…Analysis of time-series data allows to identify long term trends and make predictions that can help to improve our lives. With rapid development of artificial…”
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A Recurrent YOLOv8-based framework for Event-Based Object Detection by Silva, Diego A, Smagulova, Kamilya, Elsheikh, Ahmed, Fouda, Mohammed E, Eltawil, Ahmed M

“…Object detection is crucial in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on data from…”
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DONNA: Distributed Optimized Neural Network Allocation on CIM-Based Heterogeneous Accelerators by AlShams, Mojtaba F., Smagulova, Kamilya S., Fahmy, Suhaib A., Fouda, Mohammed E., Eltawil, Ahmed M.

“…The continued development of neural network architectures continues to drive demand for computing power. While data center scaling continues, inference away…”
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Design of CMOS-memristor Circuits for LSTM architecture by Smagulova, Kamilya, Adam, Kazybek, Krestinskaya, Olga, James, Alex Pappachen

“…Long Short-Term memory (LSTM) architecture is a well-known approach for building recurrent neural networks (RNN) useful in sequential processing of data in…”
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Event-Based Object Detection with YOLOv5 with Attention by Silva, Diego A., Smagulova, Kamilya, Fouda, Mohammed E., Eltawil, Ahmed M.

“…Event-based cameras represent a new paradigm in image processing since they operate based on asynchronous events triggered by light brightness change rather…”
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Low Power Near-sensor Coarse to Fine XOR based Memristive Edge Detection by Smagulova, Kamilya, Irmanova, Aidana, James, Alex Pappachen

“…In this paper, we propose XOR based memristive edge detector circuit that is integrated into a near sensor log-linear CMOS pixel. Memristor threshold logic was…”
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Notice of Retraction: A Linear-Logarithmic CMOS-Memristor Vision Sensor by Malikov, Timur, Smagulova, Kamilya, James, Alex Pappachen

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Memristive LSTM network hardware architecture for time-series predictive modeling problem by Adam, Kazybek, Smagulova, Kamilya, James, Alex Pappachen

“…Analysis of time-series data allows to identify long-term trends and make predictions that can help to improve our lives. With the rapid development of…”
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Resistive Neural Hardware Accelerators by Smagulova, Kamilya, Fouda, Mohammed E, Kurdahi, Fadi, Salama, Khaled, Eltawil, Ahmed

“…Deep Neural Networks (DNNs), as a subset of Machine Learning (ML) techniques, entail that real-world data can be learned and that decisions can be made in…”
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Wafer Quality Inspection using Memristive LSTM, ANN, DNN and HTM by Adam, Kazybek, Smagulova, Kamilya, Krestinskaya, Olga, James, Alex Pappachen

“…The automated wafer inspection and quality control is complex and time consuming task, which can be speed up using neuromorphic memristive architectures, as a…”
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CMOS-Memristor Hybrid Integrated Pixel Sensors by Smagulova, Kamilya, Tankimanova, Aigerim, James, Alex Pappachen

“…Increase in image resolution require the abilityof image sensors to pack an increased number of circuitcomponents in a given area. On the the other hand a high…”
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CMOS-memristor dendrite threshold circuits by Zhanbossinov, Askhat, Smagulova, Kamilya, James, Alex Pappachen

“…Non-linear neuron models overcomes the limitations of linear binary models of neurons that have the inability to compute linearly non-separable functions such…”
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