B
Benyamin Allahgholizadeh Haghi
Researcher at California Institute of Technology
Publications - 8
Citations - 130
Benyamin Allahgholizadeh Haghi is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Recurrent neural network & Artificial neural network. The author has an hindex of 4, co-authored 7 publications receiving 75 citations. Previous affiliations of Benyamin Allahgholizadeh Haghi include Sharif University of Technology & Google.
Papers
More filters
Journal ArticleDOI
Energy-Efficient Classification for Resource-Constrained Biomedical Applications
Mahsa Shoaran,Benyamin Allahgholizadeh Haghi,Milad Taghavi,Masoud Farivar,Azita Emami-Neyestanak +4 more
TL;DR: This work proposes an efficient hardware architecture to implement gradient boosted trees in applications under stringent power, area, and delay constraints, such as medical devices, and introduces the concepts of asynchronous tree operation and sequential feature extraction to achieve an unprecedented energy and area efficiency.
Proceedings ArticleDOI
Interferogram-based breast tumor classification using microwave-induced thermoacoustic imaging
TL;DR: This paper demonstrates breast tumor classification based on TA imaging based on a finite-difference time-domain (FDTD) simulation framework and proposes to use the interferogram of received pressure waves as the feature basis used for classification.
Proceedings ArticleDOI
Decoding Kinematics from Human Parietal Cortex using Neural Networks
Sahil Shah,Benyamin Allahgholizadeh Haghi,Spencer Kellis,Luke Bashford,Daniel R. Kramer,Brian J. Lee,Charles Y. Liu,Richard A. Andersen,Azita Emami +8 more
TL;DR: This work describes a BMI system using electrodes implanted in the parietal lobe of a tetraplegic subject and compares performance for four different algorithms: Kalman filter, a two-layer Deep Neural Network, a Recurrent Neural Network with SimpleRNN unit cell (SimpleRNN), and a RNN with Long-Short-Term Memory (LSTM) unit cell.
Proceedings ArticleDOI
A 41.2 nJ/class, 32-Channel On-Chip Classifier for Epileptic Seizure Detection
TL;DR: The proposed system-on-chip (SoC) breaks the strict energy-area-delay trade-off by employing area and memoryefficient techniques and achieves 27 × improvement in Energy-AreaLatency product.
Journal ArticleDOI
Unsupervised ECG Analysis: A Review
TL;DR: This study critically review and compare recent ECG clustering techniques, discusses their applications and limitations, and presents the necessary information required to adopt the appropriate algorithm for a specific application.