7 papers
Fuzzy Encoding-Decoding to Improve Spiking Q-Learning Performance in Autonomous Driving
Aref Ghoreishee, Abhishek Mishra, Lifeng Zhou +3
This paper develops an end-to-end fuzzy encoder-decoder architecture for enhancing vision-based multi-modal deep spiking Q-networks in autonomous driving. The method addresses two…
Efficient Aspect Term Extraction using Spiking Neural Network
Abhishek Kumar Mishra, Arya Somasundaram, Anup Das +1
Aspect Term Extraction (ATE) identifies aspect terms in review sentences, a key subtask of sentiment analysis. While most existing approaches use energy-intensive deep neural netwo…
New Spiking Architecture for Multi-Modal Decision-Making in Autonomous Vehicles
Aref Ghoreishee, Abhishek Mishra, Lifeng Zhou +2
This work proposes an end-to-end multi-modal reinforcement learning framework for high-level decision-making in autonomous vehicles. The framework integrates heterogeneous sensory…
Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons
Aref Ghoreishee, Abhishek Mishra, John Walsh +2
We propose a new ternary spiking neuron model to improve the representation capacity of binary spiking neurons in deep Q-learning. Although a ternary neuron model has recently been…
GPU-Accelerated Simulated Oscillator Ising/Potts Machine Solving Combinatorial Optimization Problems
Yilmaz Ege Gonul, Ceyhun Efe Kayan, Ilknur Mustafazade +2
Oscillator-based Ising machines (OIMs) and oscillator-based Potts machines (OPMs) have emerged as promising hardware accelerators for solving NP-hard combinatorial optimization pro…
Wafer2Spike: Spiking Neural Network for Wafer Map Pattern Classification
Abhishek Mishra, Suman Kumar, Anush Lingamoorthy +2
In integrated circuit design, the analysis of wafer map patterns is critical to improve yield and detect manufacturing issues. We develop Wafer2Spike, an architecture for wafer map…