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Multidimensional image morphing-fast image-based rendering of open 3D and VR environments

虚拟现实与智能硬件(中英文) 2025年第2期7卷 155-172页

作者： Simon SEIBT Bastian KUTH Bartosz von Rymon LIPINSKI Thomas CHANG Marc Erich LATOSCHIK Game Tech Laboratory Faculty of Computer ScienceNuremberg Institute of TechnologyNuremberg 90489Germany Department of Electrical Engineering and Computer Science Coburg University of Applied Sciences and ArtsCoburg 96450Germany Human-Computer Interaction Group Institute of Computer ScienceUniversity of WuerzburgWuerzburg 97074Germany

Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and ***,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains *** This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and ***,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image *** this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of *** rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image *** detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in *** addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light *** Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,*** achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering *** Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR ***,the handling of morphing artifacts in the parallax image regions remains a topic for future resea

关键词： computer graphics 3D real-time rendering computer vision Image morphing Virtual reality

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A Deep Learning Approach for Detecting Diabetic Retinopathy

A Deep Learning Approach for Detecting Diabetic Retinopathy

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2024 International Conference on computer and Applications, ICCA 2024

作者： Nabil, Mohamed Hossam Hassan Hammam, Laila Bastawrous, Hany Ayad Ebrahim, Gamal A. The British University in Egypt Electrical Engineering Department Cairo Egypt Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Ain Shams University Faculty of Engineering Computer and Systems Engineerig Department Cairo Egypt

ISBN: (纸本)9798350367560

The World Health Organization (WHO) reports that diabetic retinopathy affects one-third of diabetics, regardless of their stage of the disease. Several research efforts are focused on its automated detection and diagnosis. Identifying diabetic retinopathy is crucial due to the damage that occurs to the blood vessels of the eye retina, leading to vision blur or even complete blindness. Thus, an annual checkup is needed for people with diabetes. Moreover, uncontrolled sugar levels for diabetes patients could worsen the current stage of diabetic retinopathy. Consequently, automated detection can greatly contribute to the treatment of disease. This can be carried out through several algorithms, including deep learning models and support vector machines, in addition to transfer learning. This contribution proposes a new approach for diabetic retinopathy automated detection based on convolutional neural network (CNN) models. The proposed model provides both binary and multi-class detection. Both scenarios have shown promising results, where the training accuracies of both the binary classification and the multi-class are 92% and 94%, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Optimizing QoE in IoT-Based Video Streaming through Deep Learning Algorithms 6

Optimizing QoE in IoT-Based Video Streaming through Deep Lea...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Darwich, Mahmoud Khalil, Kasem Bayoumi, Magdy University of Mount Union Department of Mathematics and Computer Science AllianceOH44601 United States University of Mississippi Department of Electrical and Computer Engineering MS38677 United States University of Louisiana Department of Electrical and Computer Engineering LafayetteLA70504 United States

ISBN: (纸本)9798350344349

The demand for video streaming services over Internet of Things (IoT) networks has surged, yet maintaining a high Quality of Experience (QoE) remains challenging due to network heterogeneity and resource constraints. This paper presents an innovative deep learning-based approach to optimize QoE in IoT-based video streaming. Leveraging convolutional neural networks (CNN) and long short-Term memory (LSTM) networks, the proposed framework dynamically adapts video streaming parameters in real-Time, such as bit rate, frame rate, and resolution, based on the existing network conditions and device capabilities. Through extensive simulations and real-world deployments, our approach exhibited a 24.5% reduction in re-buffering ratio, a 12.5% increase in average bitrate, and a 15% improvement in video quality measured by SSIM, compared to conventional methods. Furthermore, it reduced network bandwidth consumption by up to 150% without compromising on video quality. These results underscore the effectiveness of applying deep learning algorithms to optimize video streaming in complex IoT environments. © 2024 IEEE.

关键词： Video streaming

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Weak and Extremely Low Frequency Magnetic Fields Alter the Growth Rates of HT-1080 Fibrosarcoma

Weak and Extremely Low Frequency Magnetic Fields Alter the G...

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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Dang, Nhat Keller, Jason Bajtos, Marek Gurhan, Hakki Barnes, Frank Department of Electrical Computer and Energy Engineering College of Engineering and Applied Science University of Colorado Boulder BoulderCO United States Department of Electromagnetics and Biomedical Engineering Faculty of Electrical Engineering and Information Technology University of Zilina Zilina Slovakia

ISBN: (纸本)9781946815200

This study presents experimental results showing that weak, extremely low frequency electromagnetic (EM) fields influence the growth rates of HT-1080 fibrosarcoma cells in vitro and offers a theoretical explanation for these effects. The results demonstrate that weak magnetic fields both increase and decrease the growth rates of fibrosarcoma cells by altering the mitochondrial superoxide (O2-) and calcium ions (Ca2+) concentrations in living cells. Over a 4-day exposure period, fibrosarcoma growth rates were modulated in the presence of low-level alternating current (AC) magnetic fields at a 10 μT amplitude at 13.5 Hz to 30 Hz frequency, superimposed on a 45 μT static background field. Effects due to changes in amplitude from 10 to 30 μT at selected frequencies are also investigated with the same superimposed static field. © 2025 USNC-URSI.

关键词： Electromagnetic field effects

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A System for Monitoring Hydroponic Plants in Greenhouse Using WSN, IoT and RnE 7th

A System for Monitoring Hydroponic Plants in Greenhouse Usin...

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7th International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES 2023

作者： Touhami, Achouak Bourouis, Amina Touhami, Nawal Touhami, Sana Benahmed, Tariq Benahmed, Khelifa Department of Mathematics and Computer Science Ali Kafi University Center Tindouf Algeria Department of Mathematics and Computer Science Tahri Mohammed University Bechar Algeria Department of Electrical Engineering Ahmed Draia University Adrar Algeria Department of Mathematics and Computer Science Tamaghasset University Tamaghasset Algeria

ISBN: (纸本)9783031606281

Hydroponic cultivation offers a promising solution to address environmental and food-related challenges by minimizing the use of fertilizers and water. Our research presents a greenhouse-based design for monitoring hydroponic plants, using wireless sensor networks (WSN), hydroponic irrigation system, Internet of Things (IoT) technologies and renewable energy system (RnE). The WSN consists of diverse sensors, including those for water level, water temperature, and pH levels. The sensors are connected to a cluster head, which is linked to a microcontroller. Through the Internet, the microcontroller transmits the collected data to the farmer. The farmer evaluates the data by comparing it to predetermined thresholds and, using a laptop or smartphone, sends commands to the associated actuator. The cloud serves as the storage system for the collected data. The system features automated control capabilities, allowing for adjustments in temperature, pH levels, and water levels. Furthermore, the proposed design can be easily customized to accommodate different hydroponic conditions and systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Hydroponics

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Online Container Scheduling for Data-intensive Applications in Serverless Edge Computing 42

Online Container Scheduling for Data-intensive Applications ...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Shang, Xiaojun Mao, Yingling Liu, Yu Huang, Yaodong Liu, Zhenhua Yang, Yuanyuan Stony Brook University Department of Electrical and Computer Engineering United States Shenzhen University College of Computer Science and Software Engineering Shenzhen China Stony Brook University Department of Applied Mathematics and Statistics United States

ISBN: (纸本)9798350334142

Introducing the emerging serverless paradigm into edge computing could avoid over- and under-provisioning of limited edge resources and make complex edge resource management transparent to application developers, which largely facilitates the cost-effectiveness, portability, and short time-to-market of edge applications. However, the computation/data dispersion and device/network heterogeneity of edge environments prevent current serverless computing platforms from acclimating to the network edge. In this paper, we address such challenges by formulating a container placement and data flow routing problem, which fully considers the heterogeneity of edge networks and the overhead of operating serverless platforms on resource-limited edge servers. We design an online algorithm to solve the problem. We further show its local optimum for each arriving container and prove its theoretical guarantee to the optimal offline solution. We also conduct extensive simulations based on practical experiment results to show the advantages of the proposed algorithm over existing baselines. © 2023 IEEE.

关键词： Edge computing

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Conical Transition Graphs for Analysis of Asymptotic Stability in Hybrid Dynamical Systems ⁎

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IFAC-PapersOnLine 2024年第11期58卷 159-164页

作者： Paul K. Wintz Ricardo G. Sanfelice Department of Applied Mathematics University of California Santa Cruz Department of Electrical and Computer Engineering University of California Santa Cruz

A method is proposed for analyzing asymptotic stability in the conical approximation of a hybrid system. Specifically, this paper introduces the conical transition graph (CTG) to simplify the analysis of asymptotic stability in conical approximations by converting solutions to a hybrid system into walks through a discrete graph. By exploiting the fact that pre-asymptotic stability in a conical approximation implies pre-asymptotic stability in the original system, a CTG-based approach can establish asymptotic stability in hybrid systems that have nonlinear flow maps and jump maps without needing to construct a Lyapunov function.

关键词： Stability stabilization of hybrid systems Stability of nonlinear systems

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On Some Novel Fixed Point Results for Generalized F-Contractions in b-Metric-Like Spaces with Application

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computer Modeling in engineering & Sciences 2023年第4期135卷 673-686页

作者： Kastriot Zoto Ilir Vardhami Dusan Bajovic Zoran D.Mitrovic Stojan Radenovic Department of Mathematics and Computer Sciences Faculty of Natural SciencesUniversity of GjirokastraGjirokastra6001Albania Department of Mathematics Faculty of Natural SciencesUniversity of TiranaTirana1001Albania Faculty of Electrical Engineering University of Banja LukaBanja Luka78000Bosnia and Herzegovina Department of Mathematics Faculty of Mechanical EngineeringUniversity of BelgradeBeograd11120Serbia

The focusofourwork is on themost recent results infixedpoint theoryrelated *** variants of(s,q,φ,F)-contractions that expand,supplement and unify an important work widely discussed in the literature,based on existing classes of interpolative and *** particular,a large class of contractions in terms of s,q,φand F for both linear and nonlinear contractions are defined in the framework of b-metric-like *** main result in our paper is that(s,q,φ,F)-g-weak contractions have a fixed point in b-metric-like spaces if function F or the specified contraction is *** an application of our results,we have shown the existence and uniqueness of solutions of some classes of nonlinear integral equations.

关键词： (φ,F)-contraction (s,q,φ,F)-contraction b-metric-like space fixed point

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Equivariant Frames and the Impossibility of Continuous Canonicalization 41

Equivariant Frames and the Impossibility of Continuous Canon...

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41st International Conference on Machine Learning, ICML 2024

作者： Dym, Nadav Lawrence, Hannah Siegel, Jonathan W. Faculty of Mathematics Faculty of Computer Science Technion Israel Department of Electrical Engineering and Computer Science MIT MA United States Department of Mathematics Texas A&M University TX United States

Canonicalization provides an architecture-agnostic method for enforcing equivariance, with generalizations such as frame-averaging recently gaining prominence as a lightweight and flexible alternative to equivariant architectures. Recent works have found an empirical benefit to using probabilistic frames instead, which learn weighted distributions over group elements. In this work, we provide strong theoretical justification for this phenomenon: for commonly-used groups, there is no efficiently computable choice of frame that preserves continuity of the function being averaged. In other words, unweighted frame-averaging can turn a smooth, non-symmetric function into a discontinuous, symmetric function. To address this fundamental robustness problem, we formally define and construct weighted frames, which provably preserve continuity, and demonstrate their utility by constructing efficient and continuous weighted frames for the actions of SO(d), O(d), and Sn on point clouds. Copyright 2024 by the author(s)

关键词： Probability distributions

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Semantic and spatial‐spectral feature fusion transformer network for the classification of hyperspectral image

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1308-1322页

作者： Erxin Xie Na Chen Jiangtao Peng Weiwei Sun Qian Du Xinge You Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhanChina Department of Geography and Spatial Information Techniques Ningbo UniversityNingboChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanChina

Recently,transformer‐based networks have been introduced for the classification of hyperspectral image(HSI).Although transformer‐based methods can well capture spectral sequence information,their ability to fuse different types of information contained in HSI is still *** exploit rich spectral,spatial and semantic information in HSI,a novel semantic and spatial‐spectral feature fusion transformer(S3FFT)network is proposed in this *** the proposed S3FFT method,spatial attention and efficient channel attention(ECA)modules are employed for the extraction of shallow spatialspectral ***,a transformer‐based module is designed to extract advanced fused features and to produce the pseudo‐label and class probability of each pixel for semantic feature ***,the semantic,spatial and spectral features are combined by the transformer for *** with traditional deep learning methods and recently transformer‐based methods,the proposed S3FFT shows relatively better results on three HSI datasets.

关键词： image classification machine learning

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