Hani Saleh
Khalifa University
179 Papers
635 Citations
Hani Saleh is an academic researcher from Khalifa University. The author has contributed to research in topics: Computer science & CMOS. The author has an hindex of 19, co-authored 154 publications. Previous affiliations of Hani Saleh include University of Texas at San Antonio & University of Texas at Austin.
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Papers
Efficient CNN Hardware Architecture Based on Linear Approximation and Computation Reuse Technique
Mohamed F. Tolba,Hani Saleh,Mahmoud Al-Qutayri,Ayman Hroub,Thanos Stouraitis +4 more
- 17 Dec 2023
TL;DR: An efficient hardware accelerator tailored for Convolutional Neural Networks (CNNs) is introduced, and a novel computational reuse method is presented to curtail the number of multiplication and addition operations and memory accesses, seamlessly integrated into the dedicated elements within the CNN design.
Adaptive technique for P and T wave delineation in electrocardiogram signals.
Nourhan Bayasi,Temesghen Tekeste,Hani Saleh,Ahsan H. Khandoker,Baker Mohammad,Mohammed Ismail +5 more
- 06 Nov 2014
TL;DR: This paper presents a novel robust and adaptive T and P wave delineation method for real-time analysis and nonstandard ECG morphologies, based on ECG signal filtering, value estimation of different fiducial points, applying backward and forward search windows as well as adaptive thresholds.
Computational-Based Advanced Encryption Standard (AES) Accelerator
Enas E. Abulibdeh,Hani Saleh,Baker Mohammad,Mahmoud Alqutayri +3 more
- 17 Dec 2023
TL;DR: A high-performance Advanced Encryption Standard (AES) accelerator that minimizes the area and power overhead and outperforms the standard implementation of encryption by 25% and takes the benefits of the design aspects that are utilized in it.
Combined CLT and DWT-Based ECG Feature Extractor
Temesghen Tekeste Habte,Hani Saleh,Baker Mohammad,Mohammed Ismail +3 more
- 01 Jan 2019
TL;DR: This chapter presents an ultra-low power ECG feature extraction engine based on combined techniques of CLT and DWT, fabricated using GF-65 nm technology and consumed 642 nW only when operating at a frequency of 7.5 kHz from a supply voltage of 0.6 V.
Kernel-based response extraction approach for efficient configurable ring oscillator PUF
Enas E. Abulibdeh,Hani Saleh,Baker Mohammad,Mahmoud Al-Qutayri +3 more
TL;DR: This work proposes a kernel-based response extraction approach for Configurable Ring Oscillator PUFs, reducing area and power consumption by 86% and 65.1%, respectively, while achieving strong PUF characteristics and passing NIST security tests.