162 citations
- Shiraz UniversityIR3 papers
- Xi’an Jiaotong-Liverpool UniversityCN2 papers
- Yazd UniversityIR2 papers
- Eindhoven University of TechnologyNL1 paper
- Fraunhofer Institute for Integrated CircuitsDE1 paper
- Freie Universität BerlinDE1 paper
- Friedrich-Alexander-Universität Erlangen-NürnbergDE1 paper
- Graduate University of Advanced TechnologyIR1 paper
- Institute of Mathematical SciencesIN1 paper
- Iran University of Science and TechnologyIR1 paper
- Islamic Azad University of NajafabadIR1 paper
- Korea Advanced Institute of Science and TechnologyKR1 paper
19 papers
Edge Intelligence for Wildlife Conservation: Real-Time Hornbill Call Classification Using TinyML
Kong Ka Hing, Mehran Behjati
Hornbills, an iconic species of Malaysia's biodiversity, face threats from habi-tat loss, poaching, and environmental changes, necessitating accurate and real-time population monit…
Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise
Ali Pourghoraba, MohammadSadegh KhajueeZadeh, Ali Amini +3
Reliable mechanical fault detection with limited data is crucial for the effective operation of induction machines, particularly given the real-world challenges present in industri…
The Laurent-Horner method for validated evaluation of Chebyshev expansions
Jared L. Aurentz, Behnam Hashemi
We develop a simple two-step algorithm for enclosing Chebyshev expansions whose cost is linear in terms of the polynomial degree. The algorithm first transforms the expansion from…
New logarithmic step size for stochastic gradient descent
M. Soheil Shamaee, S. Fathi Hafshejani, Z. Saeidian
In this paper, we propose a novel warm restart technique using a new logarithmic step size for the stochastic gradient descent (SGD) approach. For smooth and non-convex functions,…
Deep Learning Methods for Software Requirement Classification: A Performance Study on the PURE dataset
Fatemeh Khayashi, Behnaz Jamasb, Reza Akbari +1
Requirement engineering (RE) is the first and the most important step in software production and development. The RE is aimed to specify software requirements. One of the tasks in…
A new trigonometric kernel function for support vector machine
Sajad Fathi Hafshejani, Zahra Moberfard
In the last few years, various types of machine learning algorithms, such as Support Vector Machine (SVM), Support Vector Regression (SVR), and Non-negative Matrix Factorization (N…