3 citations · 3 across the 4 of their papers we have counts for
4 papers
ARMAN: A Reconfigurable Monolithic 3D Accelerator Architecture for Convolutional Neural Networks
Ali Sedaghatgoo, Amir M. Hajisadeghi, Mahmoud Momtazpour +1
The Convolutional Neural Network (CNN) has emerged as a powerful and versatile tool for artificial intelligence (AI) applications. Conventional computing architectures face challen…
Support for Stock Trend Prediction Using Transformers and Sentiment Analysis
Harsimrat Kaeley, Ye Qiao, Nader Bagherzadeh
Stock trend analysis has been an influential time-series prediction topic due to its lucrative and inherently chaotic nature. Many models looking to accurately predict the trend of…
Stock Trend Prediction: A Semantic Segmentation Approach
Shima Nabiee, Nader Bagherzadeh
Market financial forecasting is a trending area in deep learning. Deep learning models are capable of tackling the classic challenges in stock market data, such as its extremely co…
A Two-Stage Efficient 3-D CNN Framework for EEG Based Emotion Recognition
Ye Qiao, Mohammed Alnemari, Nader Bagherzadeh
This paper proposes a novel two-stage framework for emotion recognition using EEG data that outperforms state-of-the-art models while keeping the model size small and computational…