Gourav Datta

Orcid: 0000-0002-5380-2619

According to our database1, Gourav Datta authored at least 38 papers between 2019 and 2024.

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Bibliography

2024
Energy-Efficient & Real-Time Computer Vision with Intelligent Skipping via Reconfigurable CMOS Image Sensors.
CoRR, 2024

MaskVD: Region Masking for Efficient Video Object Detection.
CoRR, 2024

ReDistill: Residual Encoded Distillation for Peak Memory Reduction.
CoRR, 2024

Toward High Performance, Programmable Extreme-Edge Intelligence for Neuromorphic Vision Sensors utilizing Magnetic Domain Wall Motion-based MTJ.
CoRR, 2024

LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Training Ultra-Low-Latency Spiking Neural Networks from Scratch.
Proceedings of the IEEE International Conference on Acoustics, 2024

Toward High-Accuracy, Programmable Extreme-Edge Intelligence for Neuromorphic Vision Sensors utilizing Magnetic Domain Wall Motion-based MTJ.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023
Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors.
Frontiers Neuroinformatics, March, 2023

When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks.
CoRR, 2023

Spiking Neural Networks with Dynamic Time Steps for Vision Transformers.
CoRR, 2023

Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types.
CoRR, 2023

Enabling ISPless Low-Power Computer Vision.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Self-Attentive Pooling for Efficient Deep Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency.
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2023

ViTA: A Vision Transformer Inference Accelerator for Edge Applications.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

Listening Style-Aware Dyadic Facial Motion Generation.
Proceedings of the 2nd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023) co-located with the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), 2023

Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence.
Proceedings of the IEEE International Conference on Rebooting Computing, 2023

FireFly: A Synthetic Dataset for Ember Detection in Wildfire.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision.
Proceedings of the IEEE International Conference on Acoustics, 2023

Technology-Circuit-Algorithm Tri-Design for Processing-in-Pixel-in-Memory (P2M).
Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

2022
Hoyer regularizer is all you need for ultra low-latency spiking neural networks.
CoRR, 2022

Towards Energy-Efficient, Low-Latency and Accurate Spiking LSTMs.
CoRR, 2022

Enabling ISP-less Low-Power Computer Vision.
CoRR, 2022

Toward Efficient Hyperspectral Image Processing inside Camera Pixels.
CoRR, 2022

P2M: A Processing-in-Pixel-in-Memory Paradigm for Resource-Constrained TinyML Applications.
CoRR, 2022

P<sup>2</sup>M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking.
Proceedings of the 30th IFIP/IEEE 30th International Conference on Very Large Scale Integration, 2022

Asd-Transformer: Efficient Active Speaker Detection Using Self And Multimodal Transformers.
Proceedings of the IEEE International Conference on Acoustics, 2022

Towards Energy-Efficient Hyperspectral Image Processing Inside Camera Pixels.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

2021
Metastability in Superconducting Single Flux Quantum (SFQ) Logic.
IEEE Trans. Circuits Syst. I Regul. Pap., 2021

Towards Low-Latency Energy-Efficient Deep SNNs via Attention-Guided Compression.
CoRR, 2021

HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification.
CoRR, 2021

Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
qBSA: Logic Design of a 32-bit Block-Skewed RSFQ Arithmetic Logic Unit.
CoRR, 2020

Modeling and Characterization of Metastability in Single Flux Quantum (SFQ) Synchronizers.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

2019
Metastability-Resilient Synchronization FIFO for SFQ Logic.
CoRR, 2019


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