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Asymmetric Dual-Stream Networks for Lightweight RGB-D Salient Object Detection

Journal of Shanghai Jiaotong University (Science) 2025年 1-11页

作者： Wang, Yan Zheng, Wanlu Xia, Yaozheng Wang, Shaorong School of Information Science and Technology Beijing Forest University Beijing100083 China Engineering Research Center for Forestry-oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing100083 China Beijing Virtual Simulation and Visualization Engineering Center Beijing100871 China

Integrating image and depth information for RGB-D salient object detection has become a research hotspot in the field of saliency detection. Balancing the efficiency and performance of salient object detection models under resource constraints is a key challenge. To address this, this paper proposes an asymmetric lightweight network suitable for real-time RGB-D salient object detection tasks. The network reduces the number of network parameters by designing different lightweight feature extraction networks for different input modalities. Additionally, a multi-modal feature enhancement fusion module is designed to effectively fuse multi-modal features while compensating for the information loss caused by the lightweight backbone network. Moreover, this paper utilizes a global context module for dense decoding, aggregating local and global information of multi-scale features without significantly increasing computational complexity. The experimental results on five benchmarks show that the proposed lightweight RGB-D salient object detection network not only outperforms most mainstream models quantitatively and qualitatively, but also significantly outperforms other models in terms of efficiency, only with a parameter count of 5.1 million and a computational load of 0.77 gigaflops. This achievement validates the proposed method’s ability to achieve lightweight salient object detection while maintaining high efficiency. © Shanghai Jiao Tong University 2024.

关键词： Object recognition

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Semi-Automated Diabetes Prediction Using AutoGluon and TabPFN Models 1st

Semi-Automated Diabetes Prediction Using AutoGluon and TabPF...

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1st International Conference on Artificial Intelligence of Things, ICAIoT 2023

作者： Puri, Vikram Kataria, Aman Puri, Bhuvan Center of Visualization and Simulation Duy Tan University Da Nang Viet Nam CSIR-CSIO Chandigarh160030 India Lovely Professional University Jalandhar India

ISBN: (纸本)9783031487736

Since the previous decade, the number of diabetic patients has increased significantly, which raises the risk of additional complications such as heart attacks, renal failure, decreased vision, and nerve damage. If this illness is detected and treated in its early stage, patients can be saved from a life-threatening disease. The discipline of artificial intelligence (AI), which is rapidly expanding, has possibilities that could revolutionize how this serious ailment is diagnosed and managed. At present, AI can only forecast diabetes using manually entered data. This paper proposes a semi-automated AI model that allows us to measure in automated and manual ways. Additionally, the two distinct AI models, AutoGluon and TabPFN, are employed to train AI models and are assessed using statistical metrics. Additionally, it also compares with the four traditional models w.r.t evaluation performance. Feature importance is then utilized to determine which feature is more advantageous. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Homography-guided stereo matching for wide-baseline image interpolation

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Computational Visual Media 2022年第1期8卷 119-133页

作者： Yuan Chang Congyi Zhang Yisong Chen Guoping Wang Peking University Beijing 100871China Beijiing Engineering Technology Research Center of Virtual Simulation and Visualization Peking UniversityBeijing 100871China The University of Hong Kong Hong KongChina

Image interpolation has a wide range of applications such as frame rate-up conversion and free viewpoint *** significant progresses,it remains an open challenge especially for image pairs with large *** this paper,we first propose a novel optimization algorithm for motion estimation,which combines the advantages of both global optimization and a local parametric transformation *** perform optimization over dynamic label sets,which are modified after each iteration using the prior of piecewise consistency to avoid local *** we apply it to an image interpolation framework including occlusion handling and intermediate image *** validate the performance of our algorithm experimentally,and show that our approach achieves state-of-the-art performance.

关键词： image interpolation view synthesis homo-graphy propagation belief propagation

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Investigation of High-H2 Reducing Gas Delivery Through Shaft-Level Tuyeres With Computational Fluid Dynamics 1

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Advances in Pyrometallurgy Symposium, held at the TMS Annual Meeting and Exhibition, TMS 2023

作者： Okosun, Tyamo Nielson, Samuel Ugarte, Orlando Zhou, Chenn Q. Center for Innovation Through Visualization and Simulation Purdue University Northwest 2200 169th Street HammondIN46323 United States

ISBN: (数字)9783031226342

ISBN: (纸本)9783031226335

As both a significant contributor to the steelmaking process and the largest single source of CO2 emissions in integrated steelmaking, the blast furnace is a critical area of focus for decarbonization efforts. Generally, the replacement of coke with injected fuels such as natural gas or syngas has been a key pathway for reducing emissions. These injectants provide higher concentrations of H2 reducing gas, decreasing reliance on CO reactions, but they are limited by their endothermic impacts on flame and reducing gas temperature. One potential method of circumventing these limitations is the use of shaft-level tuyeres for high rates of hot reducing gas delivery, in a similar fashion to the direct-reduced ironmaking process. In this paper, the impacts of such a system are investigated with Computational Fluid Dynamics to predict the reaction rates, coke replacement ratios, and carbon emissions of the blast furnace process under the proposed operating scheme. © 2023, The Minerals, Metals & Materials Society.

关键词： Blast furnaces

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Flight Deck Design of a Hybrid Turbine/Electric Passenger Aircraft 43

Flight Deck Design of a Hybrid Turbine/Electric Passenger Ai...

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43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024

作者： Etherington, Timothy Aurthur, Trey Hill, Melissa Litt, Jonathan Simulation and Visualization Analytics Mechanics Associates HamptonVA United States Aerospace Flight Systems Branch Nasa Langley Research Center HamptonVA United States Simulation Development and Analysis Branch Nasa Langley Research Center HamptonVA United States Intelligent Control Autonomy Branch Nasa Glenn Research Center ClevlandOH United States

ISBN: (纸本)9798350349610

NASA is exploring the development of a 180-passenger subsonic single engine aft turbine aircraft, The aft turbine provides electric power in a hybrid design to wing mounted electric engines, creating a highly efficient, high-bypass-ratio fan equivalent. The SUbsonic Single Aft eNgine (SUSAN) aircraft is being developed as a sustainable subsonic regional aircraft that seeks to reduce emission levels by 50% in the next few decades. Pilot-in-the-loop studies were conducted at the NASA Langley Research center in Hampton, Virginia, to explore the flight deck design for the hybrid electric aircraft. Following modern trends in commercial aircraft flight decks with full time augmented controls and a quiet and dark philosophy, single throttle and simplified engine displays were developed for the SUSAN aircraft. The aircraft includes a single aft mounted turbine engine and 16 wing mounted electric fans. The final design was developed from feedback received during an earlier pilot-in-the-loop study where one, two, and three throttles were tested in standard airline operations, including various failures of the turbine and electric engines. Current flight deck designs normally provide control inceptors for each propulsion engine and an engine display for all primary aircraft engine parameters. With full time augmentation expected, a single throttle control with autothrottle always engaged, even during failures, is desired. Augmentation of flight controls using distributed thrust also requires full time control of the electric engines using automation. Additionally, electric engine thrust is augmented during climb based on battery state of charge. Thrust augmentation changes faster than human reaction time and therefore requires full-time automation. A pilot-in-the-loop study was conducted at the NASA Langley Research center in Hampton, Virginia, to test the final design of the single throttle with simplified engine displays. Fourteen airline pilots evaluated the single throttle

关键词： Bypass ratio

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Multi-Agent Team Access Monitoring: Environments that Benefit from Target Information Sharing

Multi-Agent Team Access Monitoring: Environments that Benefi...

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Integrated Communications, Navigation and Surveillance Conference, ICNS

作者： Andrew Dudash Scott James Ryan Rubel Noblis Autonomous Systems Research Center Reston Virginia Noblis Simulation and Visualization Research Center Reston Virginia

ISBN: (数字)9798350393095

ISBN: (纸本)9798350393101

Robotic access monitoring of multiple target areas has applications including checkpoint enforcement, surveillance and containment of fire and flood hazards. Monitoring access for a single target region has been successfully modeled as a minimum-cut problem. We generalize this model to support multiple target areas using two approaches: iterating on individual targets and examining the collections of targets holistically. Through simulation we measure the performance of each approach on different scenarios.

关键词： Navigation Surveillance Information sharing Floods Robots

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simulation of collective pursuit-evasion behavior with runtime situational awareness

Simulation of collective pursuit-evasion behavior with runti...

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作者： Yu, Zhenjing Tan, Junyin Li, Sheng School of Computer Science Peking University Beijing China Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Beijing China

We present a simulation method of pursuit-evasion behaviors between different herds with runtime situational awareness. We model the collective movement of predators and prey in the hunting process based on an improved Boid model and the finite state machine involving multiple perception factors about the situations. Taking wolves hunting caribous as an example, our method not only simulates the collective behavior, but also realizes individual intelligent behaviors consistent with the observations. We conducted intensive experiments, and the results show that our method can simulate more realistic pursuit-evasion behavior under different testing scenarios with a variety of parameters. Our method can be easily transferred to the theoretical study of collective behaviors of other herds. © 2022 John Wiley & Sons Ltd.

关键词： collective behavior perception pursuit-evasion situational awareness

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Multi-Agent Team Access Monitoring: Environments that Benefit from Target Information Sharing

arXiv

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arXiv 2024年

作者： Dudash, Andrew James, Scott Rubel, Ryan Noblis Autonomous Systems Research Center RestonVA United States Noblis Simulation and Visualization Research Center RestonVA United States

关键词： Multi agent systems

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Modeling of Macro-scale Reaction Effects in a Secondary Lead Reverberatory Furnace 1

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Symposium on Materials Processing Fundamentals, held at the TMS Annual Meeting and Exhibition, 2023

作者： Walla, Nicholas J. Higley, Emily A. Silaen, Armin K. Anderson, Alexandra Grogan, Joseph Zhou, Chenn Q. Center for Innovation through Visualization and Simulation Purdue University Northwest 2200 169th Street HammondIN46323 United States Research and Development Gopher Resource 6505 Jewel Avenue TampaFL33619 United States

ISBN: (数字)9783031226571

ISBN: (纸本)9783031226564

A long-standing and effective way to recycle lead-acid battery materials is through processing of lead compounds into lead product within a reverberatory furnace. Exploration of process and design changes through unit modification can be costly, time-consuming, and potentially harmful to operational efficiency. Modeling of process behavior, including furnace heat transfer and material reduction/decomposition, can however be difficult. To this end, a method for reflecting the production capabilities of a lead reverberatory furnace under various operational conditions has been developed. Reactions of the lead compounds have been approximated within a steady-state computational fluid dynamics simulation by adding or removing heat from the domain depending on local thermal conditions. With this, process and design changes can be explored in the simulated environment before moving onto more-advanced stages of modeling or experimentation. © The Minerals, Metals & Materials Society 2023.

关键词： Lead compounds

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APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System

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IEEE Access 2023年 11卷 74000-74020页

作者： Javed, Safdar Hussain Ahmad, Maaz Bin Asif, Muhammad Akram, Waseem Mahmood, Khalid Das, Ashok Kumar Shetty, Sachin College of Computing and Information Sciences Karachi75190 Pakistan Lahore Garrison University Department of Computer Science Lahore54810 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan International Institute of Information Technology at Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India Old Dominion University Simulation and Visualization Engineering Virginia Modeling Analysis and Simulation Center Department of Modeling SuffolkVA23435 United States Old Dominion University Center for Cybersecurity Education and Research SuffolkVA23435 United States

The objective of Advanced Persistent Threat (APT) attacks is to exploit Cyber-Physical Systems (CPSs) in combination with the Industrial Internet of Things (I-IoT) by using fast attack methods. Machine learning (ML) techniques have shown potential in identifying APT attacks in autonomous and malware detection systems. However, detecting hidden APT attacks in the I-IoT-enabled CPS domain and achieving real-time accuracy in detection present significant challenges for these techniques. To overcome these issues, a new approach is suggested that is based on the Graph Attention Network (GAN), a multi-dimensional algorithm that captures behavioral features along with the relevant information that other methods do not deliver. This approach utilizes masked self-attentional layers to address the limitations of prior Deep Learning (DL) methods that rely on convolutions. Two datasets, the DAPT2020 malware, and Edge I-IoT datasets are used to evaluate the approach, and it attains the highest detection accuracy of 96.97% and 95.97%, with prediction time of 20.56 seconds and 21.65 seconds, respectively. The GAN approach is compared to conventional ML algorithms, and simulation results demonstrate a significant performance improvement over these algorithms in the I-IoT-enabled CPS realm. © 2013 IEEE.

关键词： Real time systems

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