S2RNN: Self-Supervised Reconfigurable Neural Network Hardware Accelerator for Machine Learning Applications

K Khalil, B Dey, M Bayoumi - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Hardware implementation of neural networks is challenging due to varying application
requirements. This often necessitates creating specific Field Programmable Gate Arrays …

Random Forest Algoritmasının FPGA Üzerinde Gerçekleştirilerek Performans Analizinin Yapılması

CD Kumral, A Topal, M Ersoy, R Çolak, T Yiğit - El-Cezeri, 2022 - dergipark.org.tr
Random Forest (RF), rastgele oluşturulmuş birden çok karar ağacının çıktısını birleştiren,
regresyon ve sınıflandırma problemlerini çözmek için kullanılan bir makine öğrenme …

[PDF][PDF] Comparative analysis of efficient implementation of CNN on CPU and GPU for image processing and implementation of basic CNN operations in Verilog

SH Rajput, P Mukherji, S Avachat, A Chitnis… - 2024 - ijmit.org
ABSTRACT Artificial Neural Networks can assist machines make intelligent and smart
decisions with very limited human interference. This is because these networks can learn …

Hardware Implementation of Three-Layered Perceptron Using FPGA

R Tiwari, A Bhingarde, A Kulkarni, R Kulkarni… - … Conference on Power …, 2023 - Springer
Abstract Multi-Layered Perceptron Neural Networks (MLPNNs) are information processing
systems, designed to function like a biological brain. These are a network of highly …

[引用][C] Bilgisayar destekli fpga tabanlı sayısal sistemler deney seti tasarımı

CD Kumral - 2020 - platform.almanhal.com
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