8 papers
LiteEvent-AE: Lightweight Autoencoder for Event-Based Vision on Low-Latency Energy-Constrained Edge Devices
Riadul Islam, Joey Mule, Dhandeep Challagundla +3
Event-based vision has emerged as a promising paradigm for energy-aware artificial intelligence (AI), offering sparse, low-latency visual signals that reduce redundant data process…
Time--to--Digital Converter (TDC)--Based Resonant Compute--in--Memory for INT8 CNNs with Layer--Optimized SRAM Mapping
Dhandeep Challagundla, Ignatius Bezzam, Riadul Islam
In recent years, Compute-in-memory (CiM) architectures have emerged as a promising solution for deep neural network (NN) accelerators. Multiply-accumulate~(MAC) is considered a {\t…
TSPC-PFD: TSPC-Based Low-Power High-Resolution CMOS Phase Frequency Detector
Dhandeep Challagundla, Venkata Krishna Vamsi Sundarapu, Ignatius Bezzam +1
Phase Frequency Detectors (PFDs) are essential components in Phase-Locked Loop (PLL) and Delay-Locked Loop (DLL) systems, responsible for comparing phase and frequency differences…
EA: An Event Autoencoder for High-Speed Vision Sensing
Riadul Islam, Joey Mulé, Dhandeep Challagundla +2
High-speed vision sensing is essential for real-time perception in applications such as robotics, autonomous vehicles, and industrial automation. Traditional frame-based vision sys…
PGR-DRC: Pre-Global Routing DRC Violation Prediction Using Unsupervised Learning
Riadul Islam, Dhandeep Challagundla
Leveraging artificial intelligence (AI)-driven electronic design and automation (EDA) tools, high-performance computing, and parallelized algorithms are essential for next-generati…
Event-Based Crossing Dataset (EBCD)
Joey Mulé, Dhandeep Challagundla, Rachit Saini +1
Event-based vision revolutionizes traditional image sensing by capturing asynchronous intensity variations rather than static frames, enabling ultrafast temporal resolution, sparse…