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Kidney Tumor Detection Using MLflow, DVC and Deep Learning 2

Kidney Tumor Detection Using MLflow, DVC and Deep Learning

引用

2nd IEEE international conference on Advances in Information Technology, ICAIT 2024

作者： Usha, M.G. Shreya, M.S. Supreeth, S. Shruthi, G. Pruthviraja, Dayananda Chavan, Pundalik School of Computer Science Engineering REVA University Bangalore India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal576104 India

ISBN: (纸本)9798350383867

Kidney tumors are a global health concern, necessitating precise detection for effective treatment and better patient outcomes. This paper presents a novel approach that combines deep learning with Data Version Control (DVC) and MLflow frameworks to revolutionize kidney cancer detection. Deep learning, a subset of artificial intelligence, shows great promise in interpreting complex patterns in medical imaging data. Utilizing convolutional neural networks (CNNs), our model analyzes radiographic images to identify subtle indicators of renal malignancies with unprecedented accuracy and efficiency. Incorporating DVC ensures seamless management of large imaging datasets, promoting collaboration and reproducibility across research endeavors. Additionally, MLflow streamlines the experimentation process, enabling systematic evaluation of model performance metrics and hyperparameters. Through meticulous logging and visualization of experimentation results, our framework facilitates informed decision-making, leading to the selection of optimal models for kidney cancer detection. This comprehensive approach signifies a significant advancement in oncological diagnostics, offering a holistic solution to the challenges posed by kidney cancer. By merging deep learning with DVC and MLflow, our methodology heralds a transformative paradigm shift in cancer detection, poised to enhance clinical outcomes and elevate patient care globally. ©2024 IEEE.

关键词： Convolutional neural networks

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AR Based Educational App: A Survey 6

AR Based Educational App: A Survey

引用

6th IEEE international conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Anila, S. Shyama, R. Abhinav, R.P. Unni, Achyuth Ganesh, Gokul S Adi Shankara Institute of Engineering & Technology Computer Science and Engineering Kerala Kalady India

ISBN: (纸本)9798350381689

Augmented reality is opening up exciting new frontiers in education by seamlessly blending digital enhancements with the physical learning environment. This fusion of real and virtual creates immersive experiences where abstract concepts spring to life. Students are empowered to actively construct knowledge and collaboratively solve problems within authentic *** enables 3D visualizations that overlay physical objects, allowing learners to interact with content in entirely new ways. Detailed computer graphics respond in real-time, transforming static materials into dynamic learning tools. Educators are leveraging AR's visualization and simulation capabilities to boost engagement and deepen understanding of complex topics. This emerging technology aligns well with constructivist and situated learning theories that emphasize hands-on, contextualized learning. By leveraging mobile devices, AR makes these powerful experiences available anytime, anywhere. The educational AR market is projected to grow exponentially in the coming years, reflecting the tremendous potential of this technology to reimagine teaching and learning. Educators are increasingly embracing AR to spark curiosity,promote active inquiry and create immersive digital layers that bring the classroom to life. This fusion of cutting-edge technology with pedagogical innovation points to an exciting future for augmented learning. © 2024 IEEE.

关键词： Personnel training

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Improving Prototype Intelligent Tactical Board for Rugby Sevens 13

Improving Prototype Intelligent Tactical Board for Rugby Sev...

引用

Joint 13th international conference on Soft Computing and Intelligent Systems and 25th international Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Yashiro, Kotaro Hirose, Soma Nakada, Yohei Graduate School of Advanced Mathematical Sciences Meiji University Tokyo Japan School of Interdisciplinary Mathematical Sciences Meiji University Tokyo Japan

ISBN: (纸本)9798350373332

In the last decade, advanced tactical understanding has become increasingly necessary for players and coaches in rugby, as has been the case in other team sports. Against this background, we have prototyped an intelligent tactical board tool for rugby sevens. This tool can compute a single normative offensive sequence derived from players' position and velocity information, consisting of running plays and hand-passing plays. The computed sequence serves as a reference for enhancing the tactical understanding of players and coaches. However, considering practical usage situations, displaying multiple offensive sequences is expected to be more suitable, as it provides a broader range of options. Yet, this is difficult to achieve due to the limitations of the simple branch and bound algorithm currently applied. Therefore, in this study, we enhance this prototype tool so that it can compute multiple normative offensive sequences. Moreover, to make the computed sequences more intuitively understandable, this study newly incorporates an integration function with a commercially available 3D visualization tool for rugby plays to this prototype tool. To confirm the functionality of the improved tool, we conduct a validation test using a real formation example from a video of an actual rugby sevens match. © 2024 IEEE.

关键词： Three dimensional computer graphics

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Open-sourced real-time visualization platform for traffic simulation 14

Open-sourced real-time visualization platform for traffic si...

引用

14th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2023 and The 6th international conference on Emerging Data and Industry 4.0, EDI40 2023

作者： Jung, Jaeeun Oh, Taeho Kim, Inhi Park, Shinhyoung Kongju National University South Korea 1223-24 Cheonan-daero Seobuk-gu Chungcheongnam-do Cheonan-si31080 Korea Republic of Monash University 23 College Walk Monash University Clayton campus Victoria3168 Australia Southeast University No. 2 Southeast University Road Jiangsu Nanjing210096 China Korea Advanced Institute of Science and Technology 193 Munji-ro Yuseong-gu Daejeon34051 Korea Republic of University of Seoul 163 Seoulsiripdae-ro Dongdaemun-gu Seoul 02504 Korea Republic of

To solve the city's traffic congestion problem, micro-traffic simulation is widely used to analyze the current situation and implement a plan to solve the problem. With the nature of the simulation, it is possible to design multiple scenarios and predict future traffic conditions. The state of the network is usually represented visually through 3D graphics and numbers such as speed, delay time, etc. However, analysis results are generally not intuitive, making it difficult for non-experts to judge traffic indicators. This study presents the possibility of utilizing an open-sourced real-time web-based platform linking simulation results to dashboards. Here, the micro traffic simulation, VISSIM is used. Traffic flow at intersections and location information of individual vehicles are stored in the cloud from VISSIM at analysis intervals. In real-time, the saved results are loaded into Elasticsearch, an open-source visualization tool. Data are visualized according to temporal and spatial characteristics and constitute the dashboard layout. Users intuitively analyze and predict traffic conditions through this visualization platform. In addition, traffic conditions can be easily communicated to general users who use web-based information. © 2023 Elsevier B.V.. All rights reserved.

关键词： Smart city

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Deep Explainable Ensemble for Medical Image Analysis

Deep Explainable Ensemble for Medical Image Analysis

引用

2024 IEEE Region 10 conference, TENCON 2024

作者： Syed, Hassaan Haider Aneja, Nagender Malik, Owais Ahmed Minhaj, Mohammed Abdul Rahman School of Digital Science Universiti Brunei Darussalam Bandar Seri Begawan Brunei Purdue University Department of Computer Science West LafayetteIN United States Hospital Ripas Department of Radiology Kianggeh Brunei

ISBN: (纸本)9798350350821

Traditionally, medical images have been analyzed manually. However, this manual analysis can be subjective, depending on the judgment of radiologists and pathologists, which can result in inconsistency and inefficiency. computer vision and deep learning models have revolutionized the study and diagnosis of medical images such as X-rays, CT scans, and MRIs. Despite their effectiveness, these models often act as black boxes and are difficult to interpret. In this study, we propose an ensemble of two popular deep learning models, ResNet101 and EfficientNetB7, which not only provide higher classification accuracy for CT scans but also offer superior interpretability. Our ensemble model outperforms the original models in COVID-19 CT scan classification by more than 2%. We compared the performance of three eXplainable AI (XAI) visualization models including GradCAM, Guided-GradCAM, and LIME, against the ground truth data labeled by radiologists. The proposed ensemble method provides better interpretability for the CT scan images compared to the individual models. © 2024 IEEE.

关键词： Medical imaging

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Research on visualization of Building Information Model Based on Parametric Intelligent Technology 2

Research on Visualization of Building Information Model Base...

引用

2nd international conference on 3D Immersion, Interaction and Multi-Sensory Experiences, ICDIIME 2023

作者： Lu, Yuan Meng, Di Liu, Yuanfang East University of Heilongjiang Harbin Heilongjiang150001 China

ISBN: (纸本)9798350323818

The popularity of the Internet has overcome the space and time barriers, improved the speed and scale of information dissemination, and realized the global information exchange and sharing. In China's construction industry, it has become an industry trend to use BIM technology for related design, construction and management, which has brought about a technological revolution in the civil engineering industry. In order to promote the informatization process of the construction industry and sustainable architectural design, and improve the competitiveness of China's construction industry, the building information model (BIM) based on parameterized intelligent model technology is studied. Building information model is to use computer-aided technology to bring all stages of the construction industry into the scope of information management. This paper discusses the visualization method of building information model based on parameterized intelligent technology. Combined with the difficulties encountered by Architectural University in recent years in integrating BIM technology into the professional curriculum reform of architectural universities, this paper gives the solutions to the difficulties. © 2023 IEEE.

关键词： Information dissemination

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Hyperspectral Image visualization using PCA and Optimized Linear Stretching

Hyperspectral Image Visualization using PCA and Optimized Li...

引用

Advancement in Technology (ICONAT), international conference for

作者： Vivek Kumar Singh Tomar Tushar Kanti Patra Central Research Laboratory Ghaziabad Bhatat Electronics Limited

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

Hyperspectral images (HSI) contain many spectral bands (more than 100) which spans a wide range from 250 nm wavelength to 1500 nm and thermal Infrared. But, images can only be seen by combing Red, Green, and Blue (RGB) color bands. In this paper, we have designed an algorithm which produce pseudo color images of Hyperspectral Images, using combination of Principal Component Analysis (PCA) and Optimized Linear Stretching algorithm. Though the output image is pseudo in color but it highlight most important features as the algorithm retains top three bands, ranked in the order of information contents. Optimized Linear Stretching algorithm improves the consistent rendering of the image. Proposed method is compared with Band Selection [3] and Color Matching Function [4]. It is found to be better in maximum features retention, consistent rendering of the image and class separability.

关键词： visualization Image color analysis Color Rendering (computer graphics) Hyperspectral imaging Principal component analysis

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HawkEye-HMI-Generation: A Method to Synthesize Zoomable Process Automation User Interfaces 27

HawkEye-HMI-Generation: A Method to Synthesize Zoomable Proc...

引用

IEEE 27th international conference on Emerging Technologies and Factory Automation (ETFA)

作者： Koziolek, Heiko Hoernicke, Mario Stark, Katharina ABB Res Ladenburg Germany

ISBN: (数字)9781665499965

ISBN: (纸本)9781665499965

Process plant operators use graphical user interfaces to supervise complex processes with tens of thousands of instruments. Such systems may require more than 1000 operator screens, but an operator can only view 3-4 screens simultaneously ("keyhole-effect"), thus prolonging root cause analysis and emergency reactions. This effect contributes to the billions of USD lost in the process industry every year due to unscheduled downtimes. Researchers have proposed alternative, zoomable 2D user interfaces ("HawkEye HMIs") similar to Google Maps, to address the keyhole-effect, but manual efforts to create these HMIs proved to be cost-prohibitive. This paper proposes a novel method for HawkEye-HMI-Generation based on semi-automated page layouting and automated level-of-detail zooming, which can significantly lower graphics engineering costs. We tested a prototypical implementation on two cases from large production plants with up to 90 process graphics and more than 5000 graphical nodes, demonstrating high scalability, good usability, and a more than 70 percent cost savings potential.

关键词： Automation engineering computer-aided software visualization human machine interface zoomable user interface model-driven development

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Matrix Optimization Algorithm for WebGL-Based 3D visualization Construction Models

Matrix Optimization Algorithm for WebGL-Based 3D Visualizati...

引用

international conference on computer and Communications (ICCC)

作者： Yue Liu Ningning Xie Ledan Qin Xudong Zhang Shenyang Institute of Computing Technology University of Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

3D visualization has been widely used in various fields, from scientific computing to data analysis and virtual reality, etc., with increasingly demanding performance and quality requirements. WebGL-based 3D rendering technology brings powerful graphics processing capabilities to the Web platform, however, complex 3D models require efficient matrix operations to handle transformations, projections and view switching, etc. Traditional algorithms are difficult to strike a balance between performance and effect. In this paper, we propose an algorithm based on matrix optimization, which is specifically used to improve the computational efficiency and rendering quality of WebGL 3D visualization construction. Based on the analysis of existing algorithms, this paper proposes a strategy combining matrix decomposition and parallel optimization, and experimentally verifies its significant performance improvement in complex 3D scenes. Ultimately, the research in this paper not only improves the real-time interactive performance of 3D visualization, but also provides theoretical and practical support for future complex 3D applications based on WebGL.

关键词： Solid modeling visualization Three-dimensional displays Computational modeling Rendering (computer graphics) Real-time systems Computational efficiency Matrix decomposition Sparse matrices Optimization

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Toward Intuitive Acquisition of Occluded VR Objects Through an Interactive Disocclusion Mini-map 30

Toward Intuitive Acquisition of Occluded VR Objects Through ...

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30th IEEE conference Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Maslych, Mykola Hmaiti, Yahya Ghamandi, Ryan Leber, Paige Kattoju, Ravi Kiran Belga, Jacob LaViola, Joseph J., Jr. Univ Cent Florida ISUE Lab 4000 Cent Florida Blvd Orlando FL 32816 USA

ISBN: (纸本)9798350348156

Standard selection techniques such as ray casting fail when virtual objects are partially or fully occluded. In this paper, we present two novel approaches that combine cone-casting, world-in-miniature, and grasping metaphors to disocclude objects in the representation local to the user. Through a within-subject study where we compared 4 selection techniques across 3 levels of object occlusion, we found that our techniques outperformed an alternative one that also focuses on maintaining the spatial relationships between objects. We discuss application scenarios and future research directions for these types of selection techniques.

关键词： Human-centered computing Human computer interaction (HCI) Interaction paradigms Virtual reality Human-centered computing Human computer interaction (HCI) Interaction techniques Pointing Human-centered computing Human computer interaction (HCI) visualization miscellaneous

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