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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Junyi Wu Weitai Kang Hao Tang Yuan Hong Yan Yan Department of Computer Science Illinois Institute of Technology USA Robotics Institute Carnegie Mellon University USA Department of Computer Science University of Connecticut USA

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

To interpret Vision Transformers, post-hoc explanations assign salience scores to input pixels, providing human-understandable heatmaps. However, whether these inter-pretations reflect true rationales behind the model's output is still underexplored. To address this gap, we study the faithfulness criterion of explanations: the assigned salience scores should represent the influence of the corresponding input pixels on the model's predictions. To evaluate faithful-ness, we introduce Salience-guided Faithfulness Coefficient (SaCo), a novel evaluation metric leveraging essential in-formation of salience distribution. Specifically, we con-duct pair-wise comparisons among distinct pixel groups and then aggregate the differences in their salience scores, resulting in a coefficient that indicates the explanation's degree of faithfulness. Our explorations reveal that cur-rent metrics struggle to differentiate between advanced ex-planation methods and Random Attribution, thereby failing to capture the faithfulness property. In contrast, our pro-posed SaCo offers a reliable faithfulness measurement, es-tablishing a robust metric for interpretations. Furthermore, our SaCo demonstrates that the use of gradient and multi-layer aggregation can markedly enhance the faithfulness of attention-based explanation, shedding light on potential paths for advancing Vision Transformer explainability.

关键词： Measurement Heating systems computer vision Correlation Aggregates Predictive models Benchmark testing

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Exploiting Cross-Modal Cost Volume for Multi-sensor Depth Estimation 17th

Exploiting Cross-Modal Cost Volume for Multi-sensor Depth E...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Kim, Janghyun Shin, Ukcheol Heo, Seokyong Park, Jinsun Department of Information Convergence Engineering Pusan National University Busan Korea Republic of Robotics Institute Carnegie Mellon University Pittsburgh United States School of Computer Science and Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9789819609680

Single-modal depth estimation has shown steady improvement over the years. However, relying solely on a single imaging sensor such as RGB and near-infrared (NIR) cameras can result in unreliable and erroneous depth estimation, particularly in challenging lighting conditions such as low-light or sudden lighting change scenarios. Thereby, several approaches have leveraged multiple sensors for robust depth estimation. However, the effective fusion method that maximally utilizes multi-modal sensor information still requires further investigation. With this in mind, we propose a multi-modal cost volume fusion strategy with cross-modal attention, incorporating information from both cross-spectral and single-modality pairs. Our method initially constructs low-level cost volumes that consist of modality-specific (ı.e., single modality) and modality-invariant (ı.e., cross-spectral) volumes from multi-modal sensors. These cost volumes are then gradually fused using bidirectional cross-modal fusion and unidirectional LiDAR fusion to generate a multi-sensory cost volume. Furthermore, we introduce a straightforward domain gap reduction approach to learn modality-invariant features and depth refinement techniques through cost volume-guided propagation. Experimental results demonstrate that our method achieves SOTA (State-of-the-Art) performance under diverse environmental changes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Depth perception

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Resilient Consensus in Opinion Dynamics Under Adversarial Epidemics

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IFAC-PapersOnLine 2023年第2期56卷 1841-1846页

作者： Tatsuya Masada Yuan Wang Hideaki Ishii Department of Computer Science Tokyo Institute of Technology Yokohama Japan Department of Robotics Hunan University Changsha China

In this paper, we discuss the opinion dynamics with bounded confidence in multi-agent systems under an infection spreading environment. The dynamics of the infection spreading processes follows the so-called susceptible-infected-recovered (SIR) model. Here, the infection induces faulty behaviors in the agents whose opinions may deviate from their true opinions. Cooperating with infection suppression policies and the resilient algorithm based on the mean sub-sequence reduced (MSR) approach, resilient consensus can be attained by the regular agents within a safe region. In particular, we establish sufficient conditions for resilient consensus of opinion dynamics with large bounded confidence. A numerical example is provided to verify the effectiveness of our proposed approach.

关键词： Multi-agent systems Opinion dynamics Resilient consensus SIR epidemic model

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Collaborative Control of Aerial Robots for Inferring Human Intent from Gaze Following

Collaborative Control of Aerial Robots for Inferring Human I...

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2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Chipade, Vishnu S. Gilbert, Alia Harari, Daniel Panagou, Dimitra University of Michigan Department of Aerospace Engineering Ann ArborMI United States University of Michigan Department of Robotics Ann ArborMI United States Weizmann Institute of Science Weizmann Ai Center Department of Computer Science and Applied Math Israel

ISBN: (纸本)9798350335446

In an ideal human-robot collaboration, autonomous robots work side-by-side with humans in a joint workspace, often performing complementary tasks to the humans. A robotic ability to infer human intention and goals directly from human behavior will facilitate the collaboration and maximize its efficiency. In this paper, we focus on inferring which object the human wants picked up next, based on what the human is looking at, by visually following the human gaze and head orientation. We develop a coordination protocol for a team of aerial robots to extract effective human head and gaze cues. The aerial robots are controlled to navigate around the human and collect data that improves the detection of the human's gaze and hence the intended object to be picked up. The effectiveness of the approach is shown using simulations in AirSim, a photo-realistic simulator. © 2023 IEEE.

关键词： Antennas

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Federated Learning in Competitive EV Charging Market

Federated Learning in Competitive EV Charging Market

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Sun, Chenxi Huang, Chao Shou, Biying Huang, Jianwei Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China Department of Computer Science University of California Davis United States Department of Management Science City University of Hong Kong Hong Kong Hong Kong Shenzhen China

ISBN: (纸本)9798350396782

Federated Learning (FL) has demonstrated a significant potential to improve the quality of service (QoS) of EV charging stations. While existing studies have primarily focused on developing FL algorithms, the effect of FL on the charging stations’ operation in terms of price competition has yet to be fully understood. This paper aims to fill this gap by modeling the strategic interactions between two charging stations and EV owners as a multi-stage game. Each station first decides its FL participation strategy and charging price, and then individual EV owners decide their charging strategies. The game analysis involves solving a non-concave problem and by decomposing it into a piece-wise concave program we manage to fully characterize the equilibrium. Based on real-world datasets, our numerical results reveal an interesting insight: even if FL improves QoS, it can lead to smaller profits for both stations. The key reason is that FL intensifies the price competition between charging stations by improving stations’ QoS to a similar level. We further show that the stations will participate in FL when their data distributions are mildly dissimilar. © 2023 IEEE.

关键词： charging stations competitive pricing Electric vehicles (EV) federated learning (FL) game theory

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Analysis of Causal Factor of Driver Fatigue in the Driving in Different Driving Conditions

Analysis of Causal Factor of Driver Fatigue in the Driving i...

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International Joint Conference on Neural Networks (IJCNN)

作者： Masataka Adachi Sou Nobukawa Keiichiro Inagaki Department of Robotics Science and Engineering Chubu University Kasugai Japan Department of Computer Science Chiba Institute of Technology Narashino Japan Department of Artificial Intelligence and Robotics Chubu University Kasugai Japan

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Addressing driving fatigue is crucial among the various factors in traffic accidents. The origins of driver fatigue encompass prolonged driving, sleep deprivation, and the induction of stress inherent in driving. The causes of such driver fatigue were categorized into physical factors, including sleep deprivation and prolonged driving, and perceptional-behavioral factors such as perception of driving conditions. Numerous studies have explored technologies to detect driver fatigue in terms of relevance to sleep states, eye movements, electroencephalography (EEG) activation levels, and their functional connectivity. It was also found differences in the occurrence of driver fatigue and related theta and alpha band activity based on driving conditions. However, the factors contributing to these differences remained unexplored. This study seeks to investigate the causal relationship between driver fatigue induced in different driving environments and the corresponding brain activity. We focus on perceptional load, particularly the perception of traffic objects within the driving condition, and physical loads, such as steering, acceleration, and braking, associated with variations in driving environments. In the experiment, we evaluate the relationship between such differences in physical and mental load and the occurrence of fatigue dependent on the driving condition with considering EEG activation patterns. In the results, we found that the amount of load related to driver perception and operation inherent in driving environments plays a crucial role in driver fatigue.

关键词： Sleep Human factors Fatigue Electroencephalography Biological neural networks Accidents

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Energy-efficient and Secure Wireless Communication for Telemedicine in IoT

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computer Systems science & Engineering 2022年第12期43卷 1111-1130页

作者： Shital Joshi S.Manimurugan Ahamed Aljuhani Umar Albalawi Amer Aljaedi Department of Computer Science Oklahoma State UniversityOklahomaUSA College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Industrial Innovation and Robotics Center University of TabukTabukSaudi Arabia

The Internet of Things (IoT) represents a radical shifting paradigm fortechnological innovations as it can play critical roles in cyberspace applications invarious sectors, such as security, monitoring, medical, and environmental sectors,and also in control and industrial applications. The IoT in E-medicine unleashedthe design space for new technologies to give instant treatment to patients whilealso monitoring and tracking health conditions. This research presents a systemlevel architecture approach for IoT energy efficiency and security. The proposedarchitecture includes functional components that provide privacy managementand system security. Components in the security function group provide securecommunications through Multi-Authority Ciphertext-Policy Attributes-BasedEncryption (MA-CPABE). Because MA-CPABE is assigned to unlimited devices,presuming that the devices are reliable, the user encodes data with AdvancedEncryption Standard (AES) and protects the ABE approach using the solutionsof symmetric key. The Johnson’s algorithm with a new computation measure isused to increase network lifetime since an individual sensor node with limitedenergy represents the inevitable constraints for the broad usage of wireless sensornetworks. The optimal route from a source to destination turns out as the cornerstone for longevity of network and its sustainability. To reduce the energy consumption of networks, the evaluation measures consider the node’s residualenergy, the number of neighbors, their distance, and the link dependability. Theexperiment results demonstrate that the proposed model increases network lifeby about 12.25% (27.73%) compared to Floyd–Warshall’s, Bellman–Ford’s,and Dijkstra’s algorithms, lowering consumption of energy by eliminating thenecessity for re-routing the message as a result of connection failure.

关键词： Energy-efficiency energy consumption Internet of Things telemedicine wireless sensor networks

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Rapid Assessment of MANET Reliability Trends

Rapid Assessment of MANET Reliability Trends

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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Vladimir Gvozdev Aliya Davlieva Robert Galimov Department of Computer Science and Robotics Ufa University of Science and Technology Ufa Russia

The topological features of distributed infocommunication networks are among the key factors affecting such information safety characteristics as stability; reliability and resistance to failures and attacks. In the framework of this work, the postulate is postulated that the consequences of the security threats implementation are disconnections between the Wireless Mobile ad hoc network nodes. The metric characteristic of the consequences is a change in the system reliability indicators. The paper substantiates the possibility of using well-known methods for identifying trends to build estimates of the integral security characteristics of the Wireless Mobile ad hoc network; apparatus of order statistics; statistic indexes; linguistic variables.

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Progress Estimation of an Excavation Pit 39

Progress Estimation of an Excavation Pit

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39th International Symposium on Automation and robotics in Construction, ISARC 2022

作者： Vierling, A. Groll, T. Meckel, D. Heim, K. Walter, D. Scheidhauer, L. Körkemeyer, K. Berns, K. Department of Computer Science Robotics Research Lab University of Kaiserslautern Germany Department of Civil Engineering Construction Management University of Kaiserslautern Germany

ISBN: (纸本)9789526952420

This paper presents a method for automated excavation speed and progress estimation. First, a measure for the progress speed of an excavation pit is taken from the literature and evaluated regarding the possibility for automation. For each possible parameter, an automated extraction algorithm is presented. The used system is an autonomous excavator arm of a backhoe loader where the used hardware and software system is described. Experimental evaluation of the presented approach has been done with the autonomous system for a small trench, including multiple digging cycles. The resulting measurements seem to include some systematic errors which could be identified and suitable sanity checks could be implemented, removing the erroneous measurements. The remaining measurements were used to determine the excavation speed of the autonomous excavator arm and compared to the values of experienced and amateur operators. © 2022 International Association on Automation and robotics in Construction.

关键词： Excavation

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Robotic Anchoring System with Two Locomotion Modes for Preoperative Localization of Colorectal Cancer

Robotic Anchoring System with Two Locomotion Modes for Preop...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wang, Jiale Ren, Hao Yang, Liu Zhao, Haoxiang Zhang, Ruijia Shen, Yajing Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Kowloon Hong Kong City University of Hong Kong Department of Biomedical Engineering Kowloon Hong Kong Institute of Robotics and Automatic Information System Nankai University China

ISBN: (纸本)9781665481090

At present, colorectal cancer is one of the most prevalent cancers in the world. Colectomy serves as an effective treatment option for this disease. Preoperative localization plays a vital role in the colectomy procedure. However, traditional preoperative localization techniques have a greater risk of infection and lower accuracy. Moreover, it is difficult for the previous anchoring robots to adapt to the unstructured environment of the GI tract because of their limited movement abilities. To address these challenges, this work develops a robotic anchoring system with two locomotion modes which can anchor in the designated position. Driven by the external magnetic field, the robot can achieve slipping and flipping in the stomach. When the gradients of the field increase, the robot is triggered to deploy the anchoring mechanism in the intestine. Two in vitro experiments are conducted in the stomach and intestine phantoms. The first experiment demonstrates that the robot system can achieve both slipping and flipping in the stomach and its average position error is 2.96mm. The second experiment shows that the robot system can anchor in the designated position near the tumor and can resist a peristalsis force of 0.82N from the intestine wall. © 2024 IEEE.

关键词： Diseases

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