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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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Interaction-Aware Maneuver Intention Prediction Using Gated Mixture-of-Experts Attention Mechanism

Interaction-Aware Maneuver Intention Prediction Using Gated ...

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International Conference on Intelligent Transportation

作者： Iago Pachêco Gomes Cristiano Premebida Denis Fernando Wolf Institute of Mathematics and Computer Science University of São Paulo Brazil Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal

This paper addresses the task of predicting the behavior of traffic participants, which involves complexities such as road geometry and agent interactions. To overcome these challenges, this paper presents a novel framework called AIMP (Attention-based Interaction-aware Maneuver Prediction). AIMP utilizes interaction graphs to extract intricate interaction features from traffic scenes. The framework incorporates a Gated Mixture-of-Experts Attention Mechanism, which combines information from road geometry, interaction patterns, and motion dynamics. This fusion process also considers prior maneuver intention estimations, enhancing both explainability and informativeness. Experimental results highlight a performance enhancement (approximately 2% ∼ 9% of accuracy) of the proposed AIMP framework compared to alternative fusion methods.

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Machine learning approaches for predicting Ankle Dorsi Plantar Moments in Cerebral Palsy gait analysis: A comparative study

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Gait & Posture 2024年 113卷 198-199页

作者： Mustafa Erkam Özates Firooz Salami Sebastian I. Wolf Yunus Ziya Arslan Turkish German University Department of Electrical and Electronics Engineering- Faculty of Engineering Istanbul Turkey Heidelberg University Hospital Clinic for Orthopedics and Trauma Surgery Heidelberg Germany Turkish German University Department of Robotics and Intelligent Systems- Institute of Graduate Studies in Science and Engineering- Istanbul Turkey

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Hazard Analysis of Collaborative Automation systems: A Two-layer Approach based on Supervisory Control and Simulation

Hazard Analysis of Collaborative Automation Systems: A Two-l...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Tom P. Huck Yuvaraj Selvaraj Constantin Cronrath Christoph Ledermann Martin Fabian Bengt Lennartson Torsten Kröger Intelligent Process Automation and Robotics Lab Institute of Anthropomatics and Robotics (IAR-IPR) Karlsruhe Institute of Technology India Department of Electrical Engineering Division of Systems and Control Chalmers University of Technology Gothenburg Sweden

Safety critical systems are typically subjected to hazard analysis before commissioning to identify and analyse potentially hazardous system states that may arise during operation. Currently, hazard analysis is mainly based on human reasoning, past experiences, and simple tools such as checklists and spreadsheets. Increasing system complexity makes such approaches decreasingly suitable. Furthermore, testing-based hazard analysis is often not suitable due to high costs or dangers of physical faults. A remedy for this are model-based hazard analysis methods, which either rely on formal models or on simulation models, each with their own benefits and drawbacks. This paper proposes a two-layer approach that combines the benefits of exhaustive analysis using formal methods with detailed analysis using simulation. Unsafe behaviours that lead to unsafe states are first synthesised from a formal model of the system using Supervisory Control Theory. The result is then input to the simulation where detailed analyses using domain-specific risk metrics are performed. Though the presented approach is generally applicable, this paper demonstrates the benefits of the approach on an industrial human-robot collaboration system.

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Rock-Climbing Fish Inspired Skeleton-Embedded Rigid-Flexible Coupling Suction Disc Design for Adhesion Enhancement 16th

Rock-Climbing Fish Inspired Skeleton-Embedded Rigid-Flexible...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Tan, Wenjun Qin, Hengshen Zhang, Chuang Wang, Ruiqian Zhang, Yiwei Yang, Lianchao Chen, Qin Wang, Feifei Xi, Ning Liu, Lianqing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Chengdu Institute of Biology Chinese Academy of Sciences Sichuan Chengdu610042 China Department of Electrical and Electronic Engineering University of Hong Kong 999077 Hong Kong Emerging Technologies Institute Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Pokfulam999077 Hong Kong

ISBN: (纸本)9789819964888

Underwater high-performance biological adhesion systems have attracted increasing research interest to inspire engineered adhesion systems. Switchable underwater adhesion systems typically employ suction adhesion. However, achieving low pre-pressure negative pressure adhesion is still a challenge. An inspiring nature mode is provided by the rock-climbing fish, which needs little preload and can resist a pull-off force of 1000 times its own body weight. The pectoral and abdominal fins of rock-climbing fish have evolved to almost a flat suction cup. Through micro CT, we found that a unique skeletal network is embedded in the suction cup. This unique structure increases the stiffness of the suction cup and enhances its adhesion performance. Through numerical simulation, it was revealed that this rigid, flexible coupling structure enhances the ability of the suction cup to resist lateral pressure and increases the energy dissipation of the edge detachment of the suction cup. This work can shed light on the design of novel underwater adhesion systems and inspire underwater adhesion crawling robots. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Adhesion

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Soft Sensors for Industrial Applications: Comparison of Variables Selection Methods and Regression Models

Soft Sensors for Industrial Applications: Comparison of Vari...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Joana Leiria Rodrigo Salles Jérôme Mendes Pedro Sousa Department of Electrical and Computer Engineering University of Coimbra Institute of Systems and Robotics Coimbra Portugal Oncontrol Technologies Rua Cidade Poitiers Coimbra Portugal

The digitalization of industrial environments has enabled the development of tools that make the production process more efficient and safer. In this sense, the Soft Sensor (SS) plays a fundamental role. Through historical data and indirect measurements, it is possible to estimate the value of important variables that are difficult to measure. This paper presents the SS development process: data collection and pre-processing, variable selection, model selection for SS implementation, model training and testing, and performance evaluation. The selection of variables was made with the help of Pearson Correlation, Mutual Information, and fastTracker algorithm techniques. For the implementation of SS have been tested several models: Multiple Linear Regression, Ridge Regression, Least Absolute Shrinkage and Selection Operator, Elastic Net, Support Vector Regression and Gaussian Mixture Models. Four datasets were used to test the development of the SS.

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A Compliant Robot-Assisted Mold Polishing Application Using the Franka Emika Robot

A Compliant Robot-Assisted Mold Polishing Application Using ...

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Annual Conference of Industrial Electronics Society

作者： Michael Christopher Xenya Rui Cortesão Electrical and Computer Engineering Department Institute of Systems and Robotics University of Coimbra Coimbra Portugal FOE GCTU PMB100 Accra Ghana

Metal mold casting for many application areas remains imperfect since this involves the control of numerous factors that affect workpiece quality. Surface roughness which remains one of the many issues related to metal mold cast is often mitigated by means of grinding and polishing. As many attempts are being made to address this challenge through robot-assisted techniques, we focus on rapid mold polishing using the Franka Emika (FE) robot and its programming resources, including a built-in impedance control architecture. To accomplish the objective, mold surface segmentation is necessary. For each segment, the polishing approach is based on surface normals, relative motion, and torque sensor data. Results were obtained with open platform communication-unified architecture (opc-ua) client and server that record torque and force data. Results show that tuning internal impedance control parameters for polishing tasks is feasible.

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Strength in Diversity: Multi-Branch Representation Learning for Vehicle Re-Identification

Strength in Diversity: Multi-Branch Representation Learning ...

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International Conference on Intelligent Transportation

作者： Eurico Almeida Bruno Silva Jorge Batista Institute of Systems and Robotics University of Coimbra Coimbra Portugal Department of Electrical and Computers Engineering Faculty of Science and Technology University of Coimbra Coimbra Portugal

This paper presents an efficient and lightweight multi-branch deep architecture to improve vehicle reidentification (V-ReID). While most V-ReID work uses a combination of complex multi-branch architectures to extract robust and diversified embeddings towards re-identification, we advocate that simple and lightweight architectures can be designed to fulfill the Re-Idtask without compromising performance. We propose a combination of Grouped-convolution and Loss-Branch-Split strategies to design a multi-branch architecture that improve feature diversity and feature discriminability. We combine a ResNet50 global branch architecture with a BotNet self-attention branch architecture, both designed within a Loss-Branch-Split (LBS) strategy. We argue that specialized loss-branch-splitting helps to improve re-identification tasks by generating specialized re-identification features. A lightweight solution using grouped convolution is also proposed to mimic the learning of loss-splitting into multiple embeddings while significantly reducing the model size. In addition, we designed an improved solution to leverage additional metadata, such as camera ID and pose information, that uses 97% less parameters, further improving re-identification performance. In comparison to state-of-the-art (SoTA) methods, our approach outperforms competing solutions in Veri-776 by achieving 85.6% mAP and 97.7% CMC1 and obtains competitive results in Veri-Wild with 88.1% mAP and 96.3% CMC1. Overall, our work provides important insights into improving vehicle re-identification and presents a strong basis for other retrieval tasks. Our code is available at the link.

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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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Bifurcations and Application of the Vallis - Model 11

Bifurcations and Application of the Vallis - Model

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11th IEEE International Conference on Computational Cybernetics and Cyber-Medical systems, ICCC 2024

作者： Nagy, Balint Molnar, Gyorgy Joos, Antal Nagy, Eniko Institute of Computer Engineering University of Dunaújváros Department of Mathematics Dunaújváros Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Institute of Electrophysics Óbuda University Kandó Kálmán Faculty of Electrical Engineering Department of Natural Sciences Budapest Hungary Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary Antal Bejczy Center for Intelligent Robotics Institute of Cyberphysical Systems Óbuda University John von Neumann Faculty Budapest Hungary

ISBN: (纸本)9798350350142

Investigating chaotic systems is a fertile field considering that chaos is an exotic chapter in the theory of differential equations, and it has useful applications in the theory of communications. In this work a well-known chaotic system is investigated from the bifurcation point of view and some applications are also introduced. The data studied are also visualized for better clarity. The results observed can be helpful in the encryption methods of the implementation of different communication channels. © 2024 IEEE.

关键词： Chaotic systems

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