Efficient Hardware Accelerator Design of Non-Linear Optimization Correlative Scan Matching Algorithm in 2D LiDAR SLAM for Mobile Robots [PDF]
Sensors, 2022 Simultaneous localization and mapping (SLAM) is the major solution for constructing or updating a map of an unknown environment while simultaneously keeping track of a mobile robot’s location.
Ao Hu +9 more
doaj +2 more sources
NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark. [PDF]
Front Artif Intell, 2021 Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators.
Lu A, Peng X, Li W, Jiang H, Yu S.
europepmc +2 more sources
A Heterogeneous Hardware Accelerator for Image Classification in Embedded Systems. [PDF]
Sensors (Basel), 2021 Convolutional neural networks (CNN) have been extensively employed for image classification due to their high accuracy. However, inference is a computationally-intensive process that often requires hardware acceleration to operate in real time.
Pérez I, Figueroa M.
europepmc +2 more sources
Medha: Microcoded Hardware Accelerator for computing on Encrypted Data [PDF]
Transactions on Cryptographic Hardware and Embedded Systems, 2022 Homomorphic encryption enables computation on encrypted data, and hence it has a great potential in privacy-preserving outsourcing of computations to the cloud.
Ahmet Can Mert +6 more
doaj +2 more sources
IEEE Access, 2021 Convolutional neural networks (CNNs) have dominated image recognition and object detection models in the last few years. They can achieve the highest accuracies with several applications such as automotive and biomedical applications.
Ahmed J. Abd El-Maksoud +3 more
doaj +2 more sources
Single-Image Visibility Restoration: A Machine Learning Approach and Its 4K-Capable Hardware Accelerator. [PDF]
Sensors (Basel), 2020 In recent years, machine vision algorithms have played an influential role as core technologies in several practical applications, such as surveillance, autonomous driving, and object recognition/localization.
Ngo D, Lee S, Lee GD, Kang B.
europepmc +2 more sources
Alexandria Engineering Journal, 2022 Adoption of IoT technology without considering its security implications may expose network systems to a variety of security breaches. In network systems, IoT edge devices are a major source of security risks.
Atef Ibrahim, Fayez Gebali
doaj +2 more sources
Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements [PDF]
Scientific ReportsUnderstanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated ...
Seongyeol Kim +9 more
doaj +2 more sources
FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks With Efficient DSP and Memory Optimization [PDF]
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2023 Spiking neural networks (SNNs) have been widely used due to their strong biological interpretability and high-energy efficiency. With the introduction of the backpropagation algorithm and surrogate gradient, the structure of SNNs has become more complex,
Jindong Li +4 more
semanticscholar +1 more source
SwiftTron: An Efficient Hardware Accelerator for Quantized Transformers [PDF]
IEEE International Joint Conference on Neural Network, 2023 Transformers' compute- intensive operations pose enormous challenges for their deployment in resource- constrained EdgeAI / tiny ML devices. As an established neural network compression technique, quantization reduces the hardware computational and ...
Alberto Marchisio +5 more
semanticscholar +1 more source