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Smart Device based Initial Movement Detection of Cyclists using Convolutional Neuronal Networks
[article]
2018
arXiv
pre-print
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In this article, we focus on detecting the initial movement of cyclist using smart devices. ...
We apply residual network architectures to the task of detecting the initial starting movement of cyclists. ...
Methodology Our approach aims to detect the movement transition between waiting and moving (i.e., starting) of cyclists as early as possible using a smart device. ...
arXiv:1808.04451v1
fatcat:yowy5nm2ezhajly3puijdkuaka
Video-Based Parking Occupancy Detection for Smart Control System
2020
Applied Sciences
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To detect parking lot occupancy in outdoor environments, street light control plays a crucial role in smart surveillance applications that can perform robustly in extreme surveillance environments. ...
However, traditional parking occupancy systems are mostly implemented for outdoor environments using costly sensor-based techniques. ...
[9] presented a method using LDR sensors and image processing to detect vehicle movement. The method [10] proposed a solar energy-based and ZigBee-based system. Mumtaz et al. ...
doi:10.3390/app10031079
fatcat:c22sc2kdojblrbavz6gozqq2ia
Extended Coopetitive Soft Gating Ensemble
[article]
2020
arXiv
pre-print
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In the movement primitive forecasting of cyclists, time delays contribute to the difficulty of the prediction. ...
Moreover, the XCSGE is applied to forecast the movement state of cyclists in the context of driver assistance systems. ...
In Chapter V (Cyclists Basic Movement Detection), we apply the XCSGE to predict the motion primitives of cyclists using smart devices. A detailed evaluation of the trained models is given. ...
arXiv:2004.14026v1
fatcat:xw7a3flkrjbehagpby56emkdpm
Who is wearing me? TinyDL‐based user recognition in constrained personal devices
2021
IET Computers & Digital Techniques
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microcontroller-based devices. ...
The specific use case of automatic user recognition from data captured by a wearable device is also presented. ...
With four hidden layers and eight neurons per layer, the device outputs a warning (W) and unstable working behaviour is detected. ...
doi:10.1049/cdt2.12035
fatcat:yq5j7667r5gt5oapyxxghyv2ny
Transport-domain applications of widely used data sources in the smart transportation: A survey
[article]
2018
arXiv
pre-print
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social networks, 5) transit data with the focus on smart cards, and 6) environmental data. ...
categorized into: 1) traffic flow sensors, 2) video image processors, 3) probe people and vehicles based on Global Positioning Systems (GPS), mobile phone cellular networks, and Bluetooth, 4) location-based ...
and description such as SIFT and SURF, machine-learning based classification such as Adaboost cascade of simple features, and deep convolutional networks for image recognition). ...
arXiv:1803.10902v3
fatcat:tc67qy4x4vbtjb76qi6mbwrqy4
A Smart Context-Aware Hazard Attention System to Help People with Peripheral Vision Loss
2019
Sensors
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These features are then used to quantify the danger using five predefined hazard classes using a neural network-based classifier. ...
A different number of assistive navigation systems have been developed to help people with vision impairments using wearable and portable devices. ...
systems for object detection using deep convolutional neural networks. ...
doi:10.3390/s19071630
pmid:30959756
pmcid:PMC6480538
fatcat:uhg77tiybbbotegklzed6mfrxe
Indoor Person Identification Using a Low-Power FMCW Radar
2018
IEEE Transactions on Geoscience and Remote Sensing
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To that end, we propose a robust feature learning approach based on deep convolutional neural networks. ...
In this paper, we investigate the use of micro-Doppler signatures retrieved from a low-power radar device to identify a set of persons based on their gait characteristics. ...
Secondly, we prioritize on the use of power-efficient and compact devices that are tailored to use in a smart home environment. ...
doi:10.1109/tgrs.2018.2816812
fatcat:rt3v6hsdmbdrnmom35k7ayzwae
MARVEL - D3.1: Multimodal and privacy-aware audio-visual intelligence – initial version
2022
Zenodo
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This document describes the initial version of the methodologies pro- posed by MARVEL partners towards the realisation of the Audio, Visual and Multimodal AI Subsystem of the MARVEL architecture. ...
These include methods for Sound Event De- tection, Sound Event Localisation and Detection, Automated Audio Captioning, Visual Anomaly Detection, Visual Crowd Counting, Audio-Visual Crowd Counting, as well ...
The dataset consists of a collection of 8,732 samples MARVEL -24-June 30, 2022
ACKNOWLEDGEMENT The authors wish to thank D. Takeuchi and Y. ...
doi:10.5281/zenodo.6821317
fatcat:eia7rkk5lfbg7khs3qcat5qd3m
Resource-Constrained Machine Learning for ADAS: A Systematic Review
2020
IEEE Access
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These methods mainly focus on specific problems ranging from traffic sign and light recognition to pedestrian detection. ...
Some models are easily adapted to resource-constrained hardware, such as Support Vector Machines, while others, like Neural Networks, need more complex processes to fit into the desired hardware. ...
In [40] , authors use a SSD network [41] , with a Wide Residual (WR) network [42] as a base for detecting pedestrians, vehicles and cyclists from different datasets: KITTI, CBCL Streetscenes and Cityscapes ...
doi:10.1109/access.2020.2976513
fatcat:mgoek62t6zhp3hikgqv36ibpua
Pelican Crossing System for Control a Green Man Light with Predicted Age
2022
Matrik
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using two combined methods of the FaceNet and AgeNet. ...
The new idea of our research aims to set the adaptive time arrangement on the pelican crossing intelligent system of the traffic lights "green man" based on the age of the pedestrians with artificial intelligence ...
Furthermore, gratefully acknowledge the Laboratory of Electronics and Computer Engineer for authorization to study and utilize Gunadarma University's laboratories in Depok city, Indonesia. ...
doi:10.30812/matrik.v21i2.1508
fatcat:uqpohibqwne3dgigjdqrbbb6gq
Program
2020
2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
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In this paper, we propose the concept of integrated circuit recycling, and demonstrate a statistical health assessment method using artificial neuron network (ANN) based search tree along with an optimal ...
Depthwise separable convolution is useful for building small and lightweight networks. However, the hardware design of depthwise separable convolution unit has not been well studied. ...
results of AlexNet and convolutional neural network (CNN) model based on AlexNet. ...
doi:10.1109/icce-taiwan49838.2020.9258230
fatcat:g25vw7mzvradxna2grlzp6kgiq
State of Art IoT and Edge Embedded Systems for Real-Time Machine Vision Applications
2022
IEEE Access
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IoT and edge devices dedicated to run machine vision algorithms are usually few years lagging currently available state-of-the-art technologies for hardware accelerators. ...
ones over Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC)-based platforms. ...
FPGA-BASED IoT AND EDGE MACHINE VISION SYSTEMS Initially, FPGAs comprised large number of reprogrammable LUT which are interconnected together via local and global interconnection networks to implement ...
doi:10.1109/access.2022.3175496
fatcat:u7dp4ov5qjhxximk5xgmuigp2m
Sensors and Actuators in Smart Cities
2018
Journal of Sensor and Actuator Networks
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Ateya and Ammar Muthanna built the network model and perform the simulation process. ...
Author Contributions: Alex Adim Obinikpo and Burak Kantarci conceived and pursued the literature survey on deep learning techniques on big sensed data for smart health applications, reviewed the state ...
[48] used convolutional neural networks (CNN) for the classification and detection of the key features in Parkinson's disease based on data generated from wearable sensors. ...
doi:10.3390/jsan7010008
fatcat:pt7nkf4oaraijkmsndohahqtnq
Program
2021
2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)
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A non-overlapped implanted (NOI) non-volatile memory device is used. The NOI array is designed
to form the synapses of a convolutional neural network. ...
neural networks: single shot detector and faster region-based convolutional neural
networks. ...
doi:10.1109/icce-tw52618.2021.9602919
fatcat:aetmvxb7hfah7iuucbamos2wgu
Exploring deep learning-based architecture, strategies, applications and current trends in generic object detection: A comprehensive review
2020
IEEE Access
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Covering about 300 publications that we survey 1) region proposal-based object detection methods such as R-CNN, SPPnet, Fast R-CNN, Faster R-CNN, Mask RCN, RFCN, FPN, 2) classification / regression base ...
object detection methods such as YOLO(v2 to v5), SSD, DSSD, RetinaNet, RefineDet, CornerNet, EfficientDet, M2Det 3) Some latest detectors such as, relation network for object detection, DCN v2, NAS FPN ...
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. ...
doi:10.1109/access.2020.3021508
fatcat:guri46oiejhfzeitxuuprpmjka
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