Papers Raspberry Pi 4
“Raspberry Pi 4” 태그가 달린 논문 48편 · 필터 해제
M3D-NCA: Robust 3D Segmentation with Built-in Quality Control
Medical image segmentation relies heavily on large-scale deep learning models, such as UNet-based architectures. However, the real-world utility of such models is limited by their high computational requirements, which m…
HippocampusImage SegmentationMedical Image SegmentationRaspberry Pi 4+2YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems
We present YOLOBench, a benchmark comprised of 550+ YOLO-based object detection models on 4 different datasets and 4 different embedded hardware platforms (x86 CPU, ARM CPU, Nvidia GPU, NPU). We collect accuracy and late…
BenchmarkingCPUGPUNeural Architecture Search+4Parallelization of a new embedded application for automatic meteor detection
This article presents the methods used to parallelize a new computer vision application. The system is able to automatically detect meteor from non-stabilized cameras and noisy video sequences. The application is designe…
Raspberry Pi 4RansomAI: AI-powered Ransomware for Stealthy Encryption
Cybersecurity solutions have shown promising performance when detecting ransomware samples that use fixed algorithms and encryption rates. However, due to the current explosion of Artificial Intelligence (AI), sooner tha…
Q-LearningRaspberry Pi 4Evaluation Metrics for DNNs Compression
There is a lot of ongoing research effort into developing different techniques for neural networks compression. However, the community lacks standardised evaluation metrics, which are key to identifying the most suitable…
Neural Network CompressionObjectobject-detectionObject Detection+1TinyReptile: TinyML with Federated Meta-Learning
Tiny machine learning (TinyML) is a rapidly growing field aiming to democratize machine learning (ML) for resource-constrained microcontrollers (MCUs). Given the pervasiveness of these tiny devices, it is inherent to ask…
Federated LearningMeta-LearningRaspberry Pi 4Development, Optimization, and Deployment of Thermal Forward Vision Systems for Advance Vehicular Applications on Edge Devices
In this research work, we have proposed a thermal tiny-YOLO multi-class object detection (TTYMOD) system as a smart forward sensing system that should remain effective in all weather and harsh environmental conditions us…
Model Optimizationobject-detectionObject DetectionQuantization+1Secure Video Streaming Using Dedicated Hardware
Purpose: The purpose of this article is to present a system that enhances the security, efficiency, and reconfigurability of an Internet-of-Things (IoT) system used for surveillance and monitoring. Methods: A Multi-Proce…
CPURaspberry Pi 4SPARTAN: Sparse Hierarchical Memory for Parameter-Efficient Transformers
Fine-tuning pre-trained language models (PLMs) achieves impressive performance on a range of downstream tasks, and their sizes have consequently been getting bigger. Since a different copy of the model is required for ea…
Raspberry Pi 4Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing
For time-critical IoT applications using deep learning, inference acceleration through distributed computing is a promising approach to meet a stringent deadline. In this paper, we implement a working prototype of a new …
Distributed ComputingEdge-computingModel CompressionModel Selection+1Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report
Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus, it is very crucial to have efficient a…
Bokeh Effect RenderingDepth EstimationImage SegmentationObject Tracking+2A real-time GP based MPC for quadcopters with unknown disturbances
Gaussian Process (GP) regressions have proven to be a valuable tool to predict disturbances and model mismatches and incorporate this information into a Model Predictive Control (MPC) prediction. Unfortunately, the compu…
Model Predictive ControlRaspberry Pi 4Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design
Attention-based neural networks have become pervasive in many AI tasks. Despite their excellent algorithmic performance, the use of the attention mechanism and feed-forward network (FFN) demands excessive computational a…
CPUGPURaspberry Pi 4LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile Devices
Monocular depth estimation is an essential task in the computer vision community. While tremendous successful methods have obtained excellent results, most of them are computationally expensive and not applicable for rea…
Data AugmentationDepth EstimationMonocular Depth EstimationRaspberry Pi 4Productive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection
As Deep Neural Networks (DNNs) have become an increasingly ubiquitous workload, the range of libraries and tooling available to aid in their development and deployment has grown significantly. Scalable, production qualit…
CPUDefect DetectionGPURaspberry Pi 4ImageNet Challenging Classification with the Raspberry Pi: An Incremental Local Stochastic Gradient Descent Algorithm
With rising powerful, low-cost embedded devices, the edge computing has become an increasingly popular choice. In this paper, we propose a new incremental local stochastic gradient descent (SGD) tailored on the Raspberry…
CPUEdge-computingRaspberry Pi 4Quantum Algorithms for solving Hard Constrained Optimisation Problems
The thesis deals with Quantum Algorithms for solving Hard Constrained Optimization Problems. It shows how quantum computers can solve difficult everyday problems such as finding the best schedule for social workers or th…
Raspberry Pi 4TinyM$^2$Net: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices
With the emergence of Artificial Intelligence (AI), new attention has been given to implement AI algorithms on resource constrained tiny devices to expand the application domain of IoT. Multimodal Learning has recently b…
Classificationobject-detectionObject DetectionQuantization+1An Adaptive Device-Edge Co-Inference Framework Based on Soft Actor-Critic
Recently, the applications of deep neural network (DNN) have been very prominent in many fields such as computer vision (CV) and natural language processing (NLP) due to its superior feature extraction performance. Howev…
CPUDeep Reinforcement LearningQuantizationRaspberry Pi 4ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections
With the continuous development of neural networks for computer vision tasks, more and more network architectures have achieved outstanding success. As one of the most advanced neural network architectures, DenseNet shor…
image-classificationImage ClassificationModel CompressionRaspberry Pi 4