37 citations · 137 across the 20 of their papers we have counts for
8 papers · 1 filter
AxOMaP: Designing FPGA-based Approximate Arithmetic Operators using Mathematical Programming
Siva Satyendra Sahoo, Salim Ullah, Akash Kumar
With the increasing application of machine learning (ML) algorithms in embedded systems, there is a rising necessity to design low-cost computer arithmetic for these resource-const…
AxOCS: Scaling FPGA-based Approximate Operators using Configuration Supersampling
Siva Satyendra Sahoo, Salim Ullah, Soumyo Bhattacharjee +1
The rising usage of AI and ML-based processing across application domains has exacerbated the need for low-cost ML implementation, specifically for resource-constrained embedded sy…
Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing
Max Sponner, Julius Ott, Lorenzo Servadei +3
Radar sensors offer power-efficient solutions for always-on smart devices, but processing the data streams on resource-constrained embedded platforms remains challenging. This pape…
Magnetic Proximity induced efficient charge-to-spin conversion in large area PtSe/NiFe heterostructures
Richa Mudgal, Alka Jakhar, Pankhuri Gupta +11
As a topological Dirac semimetal with controllable spin-orbit coupling and conductivity, PtSe, a transition-metal dichalcogenide, is a promising material for several applicatio…
A Large-Scale Analysis on Self-Supervised Video Representation Learning
Akash Kumar, Ashlesha Kumar, Vibhav Vineet +1
Self-supervised learning is an effective way for label-free model pre-training, especially in the video domain where labeling is expensive. Existing self-supervised works in the vi…
Ultra-low current 10 nm spin Hall nano-oscillators
Nilamani Behera, Avinash Kumar Chaurasiya, Victor H. González +6
Nano-constriction based spin Hall nano-oscillators (SHNOs) are at the forefront of spintronics research for emerging technological applications such as oscillator-based neuromorphi…