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Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking

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Ecological Informatics 2025年 90卷

作者： Jürgen Soom Isabel Boavida Renan Leite Maria João Costa Gert Toming Mairo Leier Jeffrey A. Tuhtan Embedded AI Research Lab Tallinn University of Technology Akadeemia tee 15A Tallinn 12618 Harjumaa Estonia Department of Computer Systems Akadeemia tee 15A Tallinn 12618 Harjumaa Estonia Civil Engineering Research and Innovation for Sustainability Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Forest Research Centre TERRA Associate Laboratory School of Agriculture University of Lisbon Lisboa Portugal

The need for efficient approaches to track and assess fish behavior in rivers impacted by hydropeaking is increasing. Nonetheless, employing an automated camera system for underwater monitoring requires that the algorithms function under highly variable environmental conditions, which affect the ability to detect and assess fish size. Additionally, there is a lack of openly accessible freshwater fish classification and size estimation datasets. To address these limitations, we propose a binocular underwater fish monitoring system capable of real-time fish detection and size estimation. The system was deployed and tested over one week in two Portuguese rivers affected by hydropeaking. The week-long analysis also provided new insights regarding wild fish behavior in rivers affected by hydropeaking. Results indicate that hydropeaking strongly influences how fish may use instream flow refuges during hydropeaking. Fish were less frequently detected in the flow refuge during peak flow events, suggesting that the flow conditions created habitat instability and difficulty accessing the flow refuge. In contrast, fish in the non-hydropeaking river consistently used refuge areas, reinforcing their importance as shelter during natural flow variations. This study demonstrates the potential of a computer vision-based pipeline for real-time, fully automated fish monitoring of hydropeaking’s impacts on riverine fish. Additionally, we provide PTFish, an open dataset with 18,523 manually annotated frames featuring infrared and color video frames. These findings emphasize that automated, camera-based solutions for hydropeaking monitoring can be used to develop evidence-based mitigation strategies to sustain fish populations in rivers impacted by hydropeaking.

关键词： Fish migration Size estimation Binocular vision Hydropeaking Edge computing

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Transport complexity of data dissemination in large-scale online social networks 19

Transport complexity of data dissemination in large-scale on...

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2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： Wang, Cheng Zhu, Hangyu Wang, Chaodong Zhao, Qin Zhang, Bo Key Laboratory of Embedded Systems Service Computing Ministry of Education Tongji University Shanghai China East China Branch China Academy of Information and Communications Technology Shanghai China Department of Computer Science Shanghai Normal University Tongji University Shanghai China

ISBN: (纸本)9781450371582

In this paper, we aim to measure the transport difficulty of data dissemination in online social networks (OSNs). We focus on a usual type of interest-driven social sessions in OSNs, called Social-InterestCast, under which users autonomously determine whether to view the content from their followees depending on their interest. We define the fundamental limit of transport load as a new metric, called transport complexity, i.e., the minimally required transport load for an OSN in a given carrier network. We derive the transport complexity for Social-InterestCast sessions in a large-scale OSN in the carrier network with optimal communication architecture. The results can act as the common lower bounds on transport load for Social-InterestCast in any carrier networks. To the best of our knowledge, this is the first work to measure the transport difficulty for data dissemination in OSNs by modeling session patterns with the interest-driven characteristics. © 2019 Association for Computing Machinery.

关键词： Social networking (online)

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Random Occlusion Recovery with Noise Channel for Person Re-identification 16th

Random Occlusion Recovery with Noise Channel for Person Re-i...

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16th International Conference on Intelligent Computing, ICIC 2020

作者： Zhang, Kun Wu, Di Yuan, Changan Qin, Xiao Wu, Hongjie Zhao, Xingming Zhang, Lijun Du, Yuchuan Wang, Hanli Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Tongji University Shanghai China Guangxi Academy of Science Nanning530025 China School of Computer and Information Engineering Nanning Normal University Nanning530299 China School of Computer Science and Technology Soochow University Suzhou215006 China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China Fudan University Shanghai200433 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai China Collaborative Innovation Center of Intelligent New Energy Vehicle and School of Automotive Studies Tongji University Shanghai201804 China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Department of Transportation Engineering Tongji University Shanghai201804 China Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing and Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

ISBN: (纸本)9783030607982

Person re-identification, as the basic task of a multi-camera surveillance system, plays an important role in a variety of surveillance applications. However, the current mainstream person re-identification model based on deep learning requires a lot of labeled data, which takes a lot of time and manpower. In this study, we proposed a person re-identification method based on random occlusion recovery with noise channel. We add random occlusion blocks to the original image, use the GAN model for repair, and use the repaired image to expand the original training set. After that, the generated image is adjusted through the noise channel. Finally, we use the enhanced data set to train the baseline model. Our model achieves the state-of-the-art on Market-1501 dataset, proving that the method is effective. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Images selection and best descriptor combination for multi-shot person re-identification 10th

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10th KES International Conference on Intelligent Interactive Multimedia systems and Services, IIMSS 2017

作者： Hassen, Yousra Hadj Loukil, Kais Ouni, Tarek Jallouli, Mohamed National School of Engineers of Sfax Computer and Embedded Systems Laboratory University of Sfax 4.7 km Street of Soukra Sfax3038 Tunisia

ISBN: (纸本)9783319594798

To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply studied this area of research. Most existing researches rely only on the spatial appearance information extracted from either one (single-shot) or multiple images (multi-shot) for each person. Actually, the real person re-identification framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to select the most informative samples remain a challenging problem. In this work, an extensive comparison of descriptors of state of art associated to the proposed frame selection method is considered. Specifically, we evaluate the samples selection approach using different known descriptors. For fair comparisons, two standard datasets PRID 2011 and iLIDS-VID are used showing the effectiveness and advantages of the proposed method. © Springer International Publishing AG 2018.

关键词： Cameras

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Experimental Evaluation of a Novel Personal Assistant in Greek Language for Ambient Assisted Living Environments employing home robots

Experimental Evaluation of a Novel Personal Assistant in Gre...

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2018 South-East Europe Design Automation, computer Engineering, computer Networks and Social Media Conference, SEEDA_CECNSM 2018

作者： Spournias, Alexandros Christopoulos, Konstantinos Antonopoulos, Konstantinos Panagiotou, Christos Antonopoulos, Christos Orfanoudakis, Theofanis Voros, Nikolaos Computer and Informatics Engineering Department Embedded System Design and Application Laboratory TEI of Western Greece Antirio Greece Embedded System Design and Application Laboratory School of Science and Technology Digital Systems and Media Computing Laboratory TEI of Western Greece Hellenic Open University Patras Greece Embedded System Design and Application Laboratory TEI of Western Greece Antirio Greece School of Science and Technology Digital Systems and Media Computing Laboratory Hellenic Open University Patras Greece

ISBN: (纸本)9786188331419

A personal assistance, is a software component offering advanced Human Machine Interface (HMI) features by initiating and making a "conversations" between humans and machines. Its main objective is to identify the sentences and the context from human's question and respectively give an adequate response to the question posed. The proper response is given after analyzing the words of the question with those registered in its database. This type of application is called a personal assistant - chatbot. In this work, such an application is presented where it can be installed in any smart home as well as assisted living environment. Through the application, all automations, as well as the home robot also, are controlled by human voice in Greek language. Also, a number of auxiliary applications can be performed in the direction of better human service. © 2018 Tei of Western Macedonia.

关键词： Assisted living

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Levelling the playing field: A comprehensive comparison of visual place recognition approaches under changing conditions

arXiv

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arXiv 2019年

作者： Zaffar, Mubariz Khaliq, Ahmad Ehsan, Shoaib Milford, Michael McDonald-Maier, Klaus Embedded and Intelligent Systems Laboratory in Computer Science and Electronic Engineering department University of Essex Colchester United Kingdom Australian Centre for Robotic Vision and School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Australia

In recent years there has been significant improvement in the capability of Visual Place Recognition (VPR) methods, building on the success of both hand-crafted and learnt visual features, temporal filtering and usage of semantic scene information. The wide range of approaches and the relatively recent growth in interest in the field has meant that a wide range of datasets and assessment methodologies have been proposed, often with a focus only on precision-recall type metrics, making comparison difficult. In this paper we present a comprehensive approach to evaluating the performance of 10 state-of-the-art recently-developed VPR techniques, which utilizes three standardized metrics: (a) Matching Performance b) Matching Time c) Memory Footprint. Together this analysis provides an up-to-date and widely encompassing snapshot of the various strengths and weaknesses of contemporary approaches to the VPR problem. The aim of this work is to help move this particular research field towards a more mature and unified approach to the problem, enabling better comparison and hence more progress to be made in future research. Copyright © 2019, The Authors. All rights reserved.

关键词： Semantics

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Achieving efficient realization of kalman filter on CGRA through algorithm-architecture co-design 14th

Achieving efficient realization of kalman filter on CGRA thr...

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14th International Symposium on Applied Reconfigurable Computing, ARC 2018

作者： Merchant, Farhad Vatwani, Tarun Chattopadhyay, Anupam Raha, Soumyendu Nandy, S.K. Narayan, Ranjani Institute for Communication Technologies and Embedded Systems RWTH Aachen University Aachen Germany Hardware and Embedded Systems Lab Nanyang Technological University Singapore Singapore Scientific Computation Laboratory Indian Institute of Science Bangalore India Computer Aided Design Laboratory Indian Institute of Science Bangalore India Morphing Machines Pvt. Ltd. Bangalore India

ISBN: (纸本)9783319788890

In this paper, we present efficient realization of Kalman Filter (KF) that can achieve up to 65% of the theoretical peak performance of underlying architecture platform. KF is realized using Modified Faddeeva Algorithm (MFA) as a basic building block due to its versatility and REDEFINE Coarse Grained Reconfigurable Architecture (CGRA) is used as a platform for experiments since REDEFINE is capable of supporting realization of a set algorithmic compute structures at run-time on a Reconfigurable Data-path (RDP). We perform several hardware and software based optimizations in the realization of KF to achieve 116% improvement in terms of Gflops over the first realization of KF. Overall, with the presented approach for KF, 4-105x performance improvement in terms of Gflops/watt over several academically and commercially available realizations of KF is attained. In REDEFINE, we show that our implementation is scalable and the performance attained is commensurate with the underlying hardware resources. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Kalman filters

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Towards a power adaptation strategy in multi-core embedded devices. A case study: A HMI for wheelchair command technique

Ada User Journal

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Ada User Journal 2017年第2期38卷 105-111页

作者： Ghorbel, Agnès Amor, Nader Ben Jallouli, Mohamed Computer and Embedded Systems Laboratory Ecole Nationale d'Ingénieurs de Sfax Tunisia

Power management is one of the most important challenges in the design of today's nomad embedded systems. Power management goal is to maximize performance under a given power budget. Power management techniques should include the opportunity to balance between the demanding requirements for great computing performance/throughput and the effect of offensive power consumption and negative thermal impacts. In this paper, we propose a power management technique that aims at improving energy efficiency of multimedia embedded systems with multiple processors. This technique relies on balancing the use of both CPU cores and online deciding at what core speed to process each greedy application function. As a case study, we use a Human Machine Interface for an intelligent wheelchair control technique based on face and eyes movements. We study the challenges in power management of this application on a dual-core ARM based system. The obtained results demonstrate the effectiveness of our methodology in achieving a best performance/power saving ratio. We can decrease power consumption by 6.5% while respecting computing performance limit in term of execution time.

关键词： embedded systems

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Recognition of patient groups with sleep related disorders using bio-signal processing and deep learning

arXiv

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arXiv 2021年

作者： Jarchi, Delaram Andreu-Perez, Javier Kiani, Mehrin Vysata, Oldrich Kuchynka, Jiri Prochazka, Ales Sanei, Saeid Smart Health Technologies Group School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Embedded and Intelligent Systems Laboratory School of Computer Science and Electronics University of Essex ColchesterCO4 3SQ United Kingdom Department of Computing and Control Engineering University of Chemistry and Technology in Prague Prague 6166 28 Czech Republic Department of Neurology Faculty of Medicine in Hradec Králové Charles University Hradec Králové500 05 Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6160 00 Czech Republic School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom

Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) have been used for recognition of breathing and movement-related sleep disorders. Bio-signal processing has been performed by extracting EMG features exploiting entropy and statistical moments, in addition to developing an iterative pulse peak detection algorithm using synchrosqueezed wavelet transform (SSWT) for reliable extraction of heart rate and breathing-related features from ECG. A deep learning framework has been designed to incorporate EMG and ECG features. The framework has been used to classify four groups: healthy subjects, patients with obstructive sleep apnea (OSA), patients with restless leg syndrome (RLS) and patients with both OSA and RLS. The proposed deep learning framework produced a mean accuracy of 72% and weighted F1 score of 0.57 across subjects for our formulated four-class problem. © 2021, CC BY-NC-ND.

关键词： Wavelet transforms

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BlockLoc: Secure localization in the internet-of-things using Blockchain

arXiv

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arXiv 2019年

作者： Cheikhrouhou, Omar Koubâa, Anis College of CIT Taif University Taif Saudi Arabia Computer and Embedded Systems Laboratory University of Sfax Sfax Tunisia Prince Sultan University Saudi Arabia CISTER/INESC-TEC ISEP Portugal Gaitech Robotics China

—Several IoT applications are tightly dependent on the locations of the devices. However, localization algorithms can be easily compromised by injecting false locations. In this paper, we propose a Blockchain-based secure localization algorithm for the Internet of Things (IoT). The algorithm uses a public ledger (Blockchain) that contains nodes position and the list of their neighbor nodes. This ledger is shared among the IoT devices. Once an IoT device is localized its new position and the list of neighbor nodes are added to the Blockchain. This shared localization data will be used later by other IoT devices for their localization process. To avoid the attack where a malicious node sends a fake position, the correctness of the claimed position are verified before adding it to the Blockchain. Moreover, data exchanged between nodes (IoT devices) are signed to guarantee their authenticity and integrity. The integration of these security mechanisms into the localization process permits to exclude false data and therefore reduces the localization error. The simulation results show that adding the proposed security mechanism improves the localization accuracy of the algorithm when running in the presence of malicious nodes. Copyright © 2019, The Authors. All rights reserved.

关键词： Internet of things

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