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TECMH:Transformer-Based Cross-Modal Hashing For Fine-Grained Image-Text Retrieval

Computers, Materials & Continua 2023年第5期75卷 3713-3728页

作者： Qiqi Li Longfei Ma Zheng Jiang Mingyong Li Bo Jin College of Computer and Information Science Chongqing Normal UniversityChongqing401331China Institute of Systems and Robotics(ISR) Department of Electrical and Computer Engineering(DEEC)University of CoimbraCoimbraPortugal

In recent years,cross-modal hash retrieval has become a popular research field because of its advantages of high efficiency and low ***-modal retrieval technology can be applied to search engines,crossmodalmedical processing,*** existing main method is to use amulti-label matching paradigm to finish the retrieval ***,such methods do not use fine-grained information in the multi-modal data,which may lead to suboptimal *** avoid cross-modal matching turning into label matching,this paper proposes an end-to-end fine-grained cross-modal hash retrieval method,which can focus more on the fine-grained semantic information of multi-modal ***,the method refines the image features and no longer uses multiple labels to represent text features but uses BERT for ***,this method uses the inference capabilities of the transformer encoder to generate global fine-grained ***,in order to better judge the effect of the fine-grained model,this paper uses the datasets in the image text matching field instead of the traditional label-matching *** article experiment on Microsoft COCO(MS-COCO)and Flickr30K datasets and compare it with the previous *** experimental results show that this method can obtain more advanced results in the cross-modal hash retrieval field.

关键词： Deep learning cross-modal retrieval hash learning transformer

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A data acquisition system to capture extreme human driving behaviour

A data acquisition system to capture extreme human driving b...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Ines Rito Lima José Santos-Victor Department of Electrical and Computer Engineering Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal Institute for Systems and Robotics (ISR)) Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

Assessing and encoding human driving expertise while handling challenging events, primarily during drifts, can unveil new insights regarding the professional response to extreme driving which can be integrated into Autonomous Vehicles (AVs) safety procedures. Considering the complex and dynamic data related to both human behaviour and car devices, this research area urges the inclusion of Artificial Intelligence (AI) strategies for the extraction of interdependencies and patterns that encode human driving expertise. To do so, acquiring data that comprises the pilot and vehicle performances is of utmost importance. The present work proposes a specially designed data acquisition system to collect data regarding the vehicle dynamic movement and the associated human behaviour while driving in challenging environments. Distinct sensing devices are placed across the vehicle to retrieve the vehicle position, acceleration, angular rotation, steering orientation, among others. Data was collected from professional drivers during official racing events, and initial processing results show spatial and temporal coherence with the racing performances. The preliminary analysis of the data also reveals potentially extreme events during the race.

关键词： Performance evaluation Data acquisition Robot sensing systems Encoding Sensors Safety Data mining

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The Role of the Essential Manifold in Data Mining – An Introductory Approach 23rd

The Role of the Essential Manifold in Data Mining – An I...

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23rd International Conference on Computational Science and Its Applications, ICCSA 2023

作者： de Fátima Pina, Maria Andrade, Marina Alexandra ISCTE - IUL University Institute of Lisbon Av. das Forças Armadas Lisbon1649-026 Portugal ISLA - Santarém Superior Institute of Management and Administration of Santarém Rua Teixeira Guedes 31 Santarém2000-029 Portugal ISR - UC Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Rua Silvio Lima - Pólo II Coimbra3030-290 Portugal ISTAR - IUL Information Sciences and Technologies and Architecture Research Center University Institute of Lisbon Av. das Forças Armadas Lisbon1649-026 Portugal

ISBN: (纸本)9783031371288

Interpolating data and the application of data mining techniques in nonlinear manifolds plays a significant role in different areas of knowledge, ranging from computer vision and robotics, to industrial and medical requests, and these growing number of applications have sparked the research interest of the scientific community to these topics. The Generalized Essential manifold, briefly, Essential manifold, consisting of the product of the Grassmann manifold of all k-dimensional subspaces of Rn and the Lie group of rotations in Rn, for instance, plays an important role in the problem of recovering the structure and motion from a sequence of images, also known as stereo matching, which is a crucial problem in image processing and computer vision. A well-known recursive procedure to generate interpolating polynomial curves in Euclidean spaces is the classical De Casteljau algorithm, which is a simple and powerful tool widely used in the field of Computer Aided Geometric Design, particularly because it is essentially geometrically based. This algorithm has been generalized to geodesically complete Riemannian manifolds. Thus, having this in mind, in this work we present all the ingredients for a detailed implementation of the generalized De Casteljau algorithm to generate geometric cubic polynomials in the Essential manifold preparing the ground to solve different real interpolation problems in this manifold. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data mining

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Edge computing: A neural network implementation on an iot device 5

Edge computing: A neural network implementation on an iot de...

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5th Experiment at International Conference, exp.at 2019

作者： Barreto, Ricardo Lobo, Jorge Menezes, Paulo ISR-Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Portugal

ISBN: (纸本)9781728136370

This demonstration showcases the use of reconfigurable logic to implement edge computing for IoT devices able to provide specific information from raw data produced from some sensor, e.g. a camera or microphone, instead of the raw data itself. In what concerns the embedded processing capabilities, the focus is image processing using convolutional neuronal networks (CNN). This approach is clearly distinct from the current trends in IoT devices of using cloud computing to process the collected data. We intend a twist on the established paradigm and pursue an edge computing approach. Since we are targeting small and simple devices, we need some low power solution for the CNN computation. The demonstration will be made on a Terasic DE1 (SoC) reconfigurable system, with a field programmable gate array (FPGA), and hardwired ARM processor to build the IoT device. The collected data from the CNN computation, is transmitted using an IoT protocol to a broker. © 2019 IEEE.

关键词： Edge computing

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Adaptive Backstepping of Synergistic Hybrid Feedbacks with Application to Obstacle Avoidance

Adaptive Backstepping of Synergistic Hybrid Feedbacks with A...

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American Control Conference

作者： Pedro Casau Ricardo G. Sanfelice Carlos Silvestre Institute for Systems and Robotics (ISR) Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal University of California Santa Cruz CA 95064 USA Department of Electrical and Computer Engineering of the Faculty of Science and Technology of the University of Macau Macau China

ISBN: (纸本)9781538679012;9781538679265

In this paper, we show that the hybrid controller that is induced by a Synergistic Lyapunov Function and Feedback (SLFF) pair relative to a compact set, can be extended to the case where the original affine control system is subject to a class of additive disturbances known as matched uncertainties, provided that the estimator dynamics do not add new equilibria to the closed-loop system. We also show that the proposed adaptive hybrid controller is amenable to backstepping. Finally, we apply the proposed hybrid control strategy to the problem of global asymptotic stabilization of a compact set in the presence of an obstacle and we illustrate this application by means of simulation results.

关键词： Obstacle avoidance Backstepping Feedback Collision avoidance Liapunov function control systems Closed loop systems Self tuning Controllers

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Robot-Assisted Navigation for a Robotic Walker with Aided User Intent

Robot-Assisted Navigation for a Robotic Walker with Aided Us...

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IEEE International Symposium on Robot and Human Interactive Communication

作者： Luis Garrote Joao Paulo Joao Perdiz Paulo Peixoto Urbano J. Nunes Institute of Systems and Robotics (ISR-UC) Electrical and Computer Engineering Department (DEEC-UC) University of Coimbra

ISBN: (纸本)9781538679814

This paper presents an approach to robot-assisted navigation on a mobility assistance context, by learning from the user while helping him navigate efficiently and safely in complex environments. Assistive robots such as robotic walkers provide the ability to support a user's body weight on the upper limbs while walking. However, walkers can add an extra layer of distress due to their specific manipulation constraints. For the users of such devices, lack of dexterous upper limb control can be a considerable problem as it means they may be unable to operate these devices efficiently;users may also have visual impairments that reduce their navigational efficiency. The proposed approach uses a Reinforcement Learning (RL) model and a dynamic window-based local motion planning algorithm. It aims to learn needed corrections in the motion command based on the surrounding environment and the user's intent. The proposed solution handles corrections and guides the user through the environment without collisions while learning and aiding the user when he is unable to operate the device efficiently. The RL based approach was tested in indoor scenarios with a robotic walker platform showing preliminary promising results.

关键词： Consumers Walkers Learning Upper Extremity Visual Impairment ambient environment navigation Pedestrians Distress Stressing Environments

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Discrete-time distributed Kalman filter design for multi-vehicle systems

Discrete-time distributed Kalman filter design for multi-veh...

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American Control Conference

作者： Daniel Viegas Pedro Batista Paulo Oliveira Carlos Silvestre Department of Electrical and Computer Engineering of the Faculty of Science and Technology of the University of Macau China Institute for Systems and Robotics (ISR) Instituto Superior Tecnico Universidade de Lisboa Portugal ISR and IDMEC Instituto Superior Tecnico Universidade de Lisboa Portugal

ISBN: (纸本)9781509045839

This paper addresses the problem of distributed state estimation in a multi-vehicle framework. In the scenario envisioned in this work, each vehicle aims to estimate its own state by implementing a local state observer which relies on locally available measurements and limited communication with other vehicles in the vicinity. The dynamics of the problem are formulated as a more general discrete-time Kalman filtering problem with a sparsity constraint on the gain and, based on this formulation, a method for computation of steady-state observer gains for arbitrary fixed measurement topologies is introduced. The proposed method consists in the optimization of the time-varying distributed Kalman filter over a finite time window to approximate steady-state behavior and compute well-performing steady-state observer gains. To assess the performance of the proposed solution, simulation results are detailed for the practical case of a formation of Autonomous Underwater Vehicles (AUVs).

关键词： discrete-time Kalman filters Observers State estimation Distribute vehicle filter design Time windows Steady state Autonomous underwater vehicles space vehicle system Launching vehicle systems

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3D Object Tracking using RGB and LIDAR Data

3D Object Tracking using RGB and LIDAR Data

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IEEE International Conference on Intelligent Transportation systems

作者： Alireza Asvadi Pedro Girao Paulo Peixoto Urbano Nunes Institute of Systems and Robotics (ISR) Department of Electrical and Computer Engineering (DEEC) University of Coimbra

ISBN: (纸本)9781509018901

Object tracking is one of the key components of the perception system of autonomous cars and ADASs. With tracking, an ego-vehicle can make a prediction about the location of surrounding objects in the next time epoch and plan for next actions. Object tracking algorithms typically rely on sensory data (from RGB cameras or LIDAR). In fact, the integration of 2D-RGB camera images and 3D-LIDAR data can provide some distinct benefits. This paper proposes a 3D object tracking algorithm using a 3D-LIDAR, an RGB camera and INS (GPS/IMU) sensors data by analyzing sequential 2D-RGB, 3D point-cloud, and the ego-vehicle's localization data and outputs the trajectory of the tracked object, an estimation of its current velocity, and its predicted location in the 3D world coordinate system in the next time-step. Tracking starts with a known initial 3D bounding box for the object. Two parallel mean-shift algorithms are applied for object detection and localization in the 2D image and 3D point-cloud, followed by a robust 2D/3D Kalman filter based fusion and tracking. Reported results, from both quantitative and qualitative experiments using the KITTI database demonstrate the applicability and efficiency of the proposed approach in driving environments.

关键词： red-green-blue colour model Lidar two dimentional images Cameras Current velocity Object detection Three Dimensions tracking objects

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Influence of slot geometry on air gap magnetic flux density of rotating machines 16

Influence of slot geometry on air gap magnetic flux density ...

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16th International Conference on Environment and electrical engineering, EEEIC 2016

作者： De Lima, Rodrigo Alves Coimbra, A. C. Paulo Almeida, Tony Gomes, Viviane Margarida Pereira, Thiago Martins Alves, Aylton Jose Calixto, Wesley Pacheco Program in Electronic Systems and Automation PGEA Department of Electrical Engineering ENE University of Brasilia UnB Brazil Institute of Systems and Robotics ISR University of Coimbra UC Portugal Experimental and Technological Research and Study Group NExT Federal Institute of Goias IFG Brazil

ISBN: (纸本)9781509023196

The objective of this work is to investigate the influence of slotted air gap constructive parameters on magnetic flux density of rotating machines. For this purpose, different approaches were used to solve the air gap field diagram using finite element method and the magnetic field distribution uniformity was evaluated by Carter's factor calculation. Sensitivity analysis of slot constructive parameters was performed and results show that slot geometry modifies the magnetic flux on air gap and shifts the air gap magnetic equipotential midline of double slotted machines. © 2016 IEEE.

关键词： Finite element method

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Webcam-Based Tachometer for In-Field Induction Motor Load Estimation

Webcam-Based Tachometer for In-Field Induction Motor Load Es...

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International Conference on electrical Machines

作者： Fernando J. T. E. Ferreira Fernando J. P. Lopes Institute of Systems and Robotics (ISR-UC) Department of Electrical and Computer Engineering University of Coimbra Dep. of Electrical Engineering Polytechnic Institute of Coimbra (IPC/ISEC)

ISBN: (纸本)9781509025398

Rotational speed measurement is a key issue in most industries, either for process control, characterization or fault diagnosis. In electric motor driven systems it can be used, for example, to estimate the motor load or pulley-belt transmission slip. Encoders and resolvers are typically used for continuous speed monitoring, requiring mechanical coupling with the rotating shaft/part. If the speed is to be measured at a given instant or during a few moments, noninvasive contactless optical tachometers can be used, using optical reflection or stroboscopic principles. In most cases, stroboscopic tachometers require no reflective elements/strips in the rotating part. However, if the user wants to continuously measure the speed of a given rotating part during the audit/characterization period, with real-time data logging and without sticking reflective strips or introducing shaft-coupled encoders/resolvers, there is no low-cost commercial solution to perform such task. For example, if the user's aim is to continuously estimate the load variation of an induction motor over a day or week, on the basis of the slip/speed value, it is not possible with conventional commercial low-cost contactless equipment, unless the user uses expensive online-operation equipment estimating the speed by means of input voltage/current. Moreover, in some rotating systems/parts not directly driven by an electric motor, the online equipment cannot be used and it is not practical, and in some cases even impossible, to couple an encoder/resolver or stick some reflective strips. In this paper, an innovative nonintrusive low-cost webcam-based tachometer is proposed, developed and experimentally tested. It can be used to easily estimate and record the speed over time in, for example, electrical motors, pulleys, shafts and wind turbines.

关键词： In-field speed measurement Motor speed Noninvasive speed measurement Rotational speed Tachometer Video camera Webcam Motor load estimation

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