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Smart Device based Initial Movement Detection of Cyclists using Convolutional Neuronal Networks [article]

Jan Schneegans, Maarten Bieshaar
2018 arXiv   pre-print
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

Chen, Sheu, Peng, Wu, Tseng
2020 Applied Sciences  
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]

Stephan Deist, Jens Schreiber, Maarten Bieshaar, Bernhard Sick
2020 arXiv   pre-print
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

Ramon Sanchez‐Iborra, Antonio Skarmeta
2021 IET Computers & Digital Techniques  
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]

Sina Dabiri, Kevin Heaslip
2018 arXiv   pre-print
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

Ola Younis, Waleed Al-Nuaimy, Fiona Rowe, Mohammad Alomari
2019 Sensors  
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

Baptist Vandersmissen, Nicolas Knudde, Azarakhsh Jalalvand, Ivo Couckuyt, Andre Bourdoux, Wesley De Neve, Tom Dhaene
2018 IEEE Transactions on Geoscience and Remote Sensing  
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

Alexandros Iosifidis
2022 Zenodo  
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

Juan Borrego-Carazo, David Castells-Rufas, Ernesto Biempica, Jordi Carrabina
2020 IEEE Access  
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

Purnawarman Musa, Eri Prasetyo Wibowo, Saiful Bahri Musa, Iqbal Baihaqi
2022 Matrik  
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


2020 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)  
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

Mahmoud Meribout, Asma Baobaid, Mohammed Ould Khaoua, Varun Kumar Tiwari, Juan Pablo Pena
2022 IEEE Access  
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

Mohammad Hammoudeh, Mounir Arioua
2018 Journal of Sensor and Actuator Networks  
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


2021 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)  
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

Lubna Aziz, Sah bin Haji Salam, Sara Ayub
2020 IEEE Access  
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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