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共 18124 条记录，以下是291-300 订阅

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EEG VMamba: vision Mamba for seizure prediction based on EEG 24

EEG VMamba: Vision Mamba for seizure prediction based on EEG

引用

6th international conference on Video signal and Image processing

作者： Deng, Qi Wang, Qun Liu, Weicheng Xue, Yu Beijing Inst Technol Sch Integrated Circuits & Elect Beijing Peoples R China

ISBN: (纸本)9798400709647

Epileptic seizure prediction algorithms based on EEG signals can help epilepsy patients take timely measures to avoid risks. However, EEG signals possess high dimensionality, nonlinearity, and strong temporal dependencies, making it difficult for models to integrate global and local features and capture long-term dependencies. To address these issues, we propose EEG VMamba, which use the Visual State Space (VSS) block as the backbone and introduce Convolutional Neural Network (CNN) at the later stage. This approach fully combining the local perception capability of CNN and the global modeling capability of VSS. It was evaluated on the publicly available CHB-MIT dataset to demonstrate its effectiveness in seizure prediction, achieving a sensitivity of 91.1% and an AUC of 0.914. Compared to the seizure prediction method based on vision Transformer, the EEG VMamba demonstrates superior performance, evidenced by higher sensitivity and AUC score.

关键词： EEG signals seizure prediction VSS CNN

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Investigating Effects of Multimodal Topic-continuance Recognition on Human-robot Interviewing Interaction 24

Investigating Effects of Multimodal Topic-continuance Recogn...

引用

19th Annual ACM/IEEE international conference on Human-robot Interaction (HRI)

作者： Nagasawa, Fuminori Okada, Shogo Japan Adv Inst Sci & Technol Nomi Shi Japan

ISBN: (纸本)9798400703232

This study's long-term goal is the development of a communication robot as a partner that can keep talking about specific things about which the user would like to talk and in which they are interested. To achieve this goal, we developed an interviewer robot that adapts topics based on the user's multimodal attitudes. The robot, utilizing the Japanese GPT-NeoX-3.6, selects questions based on the estimated topic continuance level. We regard the topic continuance level as the degree of the user's speaking willingness (willingness to continue the current topic). This paper aims to validate the multimodal topic continuance recognition model and its adaptive question selection strategy. First, we trained the model on the "Hazumi" dialog corpus, which includes user multimodal behavior in human-virtual agent interactions. Second, 10 participants were interviewed with the robot equipped with the trained model. After the interviews, we asked the participants if the topic continuance/change by the robot was appropriate and validated the estimation accuracy.

关键词： Human robot interaction Interview agent Multimodal machine learning Social signal processing Speaker's willingness

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Path Correction of Membrane Water-Cooled Wall Climbing robot Based on Laser vision 5

Path Correction of Membrane Water-Cooled Wall Climbing Robot...

引用

5th international conference on Electronic Engineering and Informatics, ICEEI 2023

作者： Liang, Yun Song, Jie Cheng, Xun Ying, Zhihong Huang, Songlin Chn Energy Jiujiang Power Generation Co. LTD. Jiangxi Jiujiang332000 China

ISBN: (纸本)9781643685021

To ensure that the wall-climbing robot can accurately walk along the predetermined straight route, it is necessary to obtain the real-time offset and deflection of the wall-climbing robot to provide information feedback for the control system. A set of double crosshair laser vision systems and corresponding image processing processes are designed, which controls the wall climbing robot with the center point between the cross intersections as the origin. The obtained offset and deflection are independent of each other, which can reduce the difficulty of control. Through the image processing method, the connection points between laser lines, fins, and water-cooled pipes can be effectively obtained, and then the offset and deflection amount can be calculated according to the obtained connection points. The average deviations between the offset and deflection obtained by the algorithm and the actual measurement are 0.74 mm and 0.9° respectively. © 2024 The Authors.

关键词： Deflection (structures)

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Performance Indicators for the robotics Engineering Operational Scheduling 3

Performance Indicators for the Robotics Engineering Operatio...

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3rd IEEE international conference on Intelligent Techniques in Control, Optimization and signal processing, INCOS 2024

作者： Maragathasundari, S. Jahnavi, G Meka. Vanalakshmi, R. Karthikeyan, K. Department of Engineering Mathematics Tamilnadu Chennai India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Krishnankoil India Sri Kaliswari College Department of Mathematics Tamilnadu Sivakasi India Velammal Institute of Technology Department of Mathematics Tamilnadu Chennai India

ISBN: (纸本)9798350361186

This study examines multi-stage robotic production line performance via queuing analysis to enable more accurate resource planning. It is one of a select few studies of this type designed to boost the efficiency of manufacturing robots with many stages. The goal of this study is to assist managers in increasing productivity and effectiveness while choosing the best policy for assembly systems. The study utilizes an analytical methodology based on actual data from a firm that manufactures robots. The process of making a robot involves several different processes, including identifying the problem, researching and designing the solution, developing a prototype, building the robot, programming and testing the robot, and ultimately assessing the robot. The necessary information for each workstation was gathered, and the Supplementary Variable approach was used to ascertain the processing component arrival and departure distribution statistics. The queueing analysis presented in this work serves as a foundation for predicting and analyzing production systems using metrics like utilization, the proportion of idle workstations, the number of batches in the system, the number of batches in the queue, the expected time spent in the queue, and the expected time spent in the system. © 2024 IEEE.

关键词： robot programming

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LT-VIT: A vision TRANSFORMER FOR MULTI-LABEL CHEST X-RAY CLASSIFICATION 30

LT-VIT: A VISION TRANSFORMER FOR MULTI-LABEL CHEST X-RAY CLA...

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30th IEEE international conference on Image processing (ICIP)

作者： Marikkar, Umar Atito, Sara Awais, Muhammad Mahdi, Adam Univ Surrey Surrey Inst People Ctr AI Guildford Surrey England Univ Surrey Ctr Vis Speech & Signal Proc CVSSP Guildford Surrey England Univ Oxford Oxford Internet Inst Oxford England

ISBN: (纸本)9781728198354

vision Transformers (ViTs) are widely adopted in medical imaging tasks, and some existing efforts have been directed towards vision-language training for Chest X-rays (CXRs). However, we envision that there still exists a potential for improvement in vision-only training for CXRs using ViTs, by aggregating information from multiple scales, which has been proven beneficial for non-transformer networks. Hence, we have developed LT-ViT, a transformer that utilizes combined attention between image tokens and randomly initialized auxiliary tokens that represent labels. Our experiments demonstrate that LT-ViT (1) surpasses the state-of-the-art performance using pure ViTs on two publicly available CXR datasets, (2) is generalizable to other pre-training methods and therefore is agnostic to model initialization, and (3) enables model interpretability without grad-cam and its variants.

关键词： transformers medical imaging multilabel classification

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ExAug: robot-Conditioned Navigation Policies via Geometric Experience Augmentation

ExAug: Robot-Conditioned Navigation Policies via Geometric E...

引用

IEEE international conference on robotics and Automation (ICRA)

作者： Hirose, Noriaki Shah, Dhruv Sridhar, Ajay Levine, Sergey Univ Calif Berkeley Berkeley CA 94720 USA Toyota Motor North Amer Plano TX 75024 USA

ISBN: (纸本)9798350323658

Machine learning techniques rely on large and diverse datasets for generalization. Computer vision, natural language processing, and other applications can often reuse public datasets to train many different models. However, due to differences in physical configurations, it is challenging to leverage public datasets for training robotic control policies on new robot platforms or for new tasks. In this work, we propose a novel framework, ExAug to augment the experiences of different robot platforms from multiple datasets in diverse environments. ExAug leverages a simple principle: by extracting 3D information in the form of a point cloud, we can create much more complex and structured augmentations, utilizing both generating synthetic images and geometric-aware penalization that would have been suitable in the same situation for a different robot, with different size, turning radius, and camera placement. The trained policy is evaluated on two new robot platforms with three different cameras in indoor and outdoor environments with obstacles.

关键词： Cameras

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REAL-TIME SEMANTIC VIDEO COMMUNICATION OF GENERAL SCENES 31

REAL-TIME SEMANTIC VIDEO COMMUNICATION OF GENERAL SCENES

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2024 international conference on Image processing

作者： Eteke, Cem Griessel, Alexander Kellerer, Wolfgang Steinbach, Eckehard Tech Univ Munich Sch Computat Informat & Technol Chair Media Technol D-80333 Munich Germany Tech Univ Munich Sch Computat Informat & Technol Chair Commun Networks D-80333 Munich Germany Tech Univ Munich Sch Computat Informat & Technol Munich Inst Robot & Machine Intelligence D-80333 Munich Germany

ISBN: (纸本)9798350349405;9798350349399

This paper presents a real-time semantic video communication method for general scenes, combining lossy semantic map coding with motion compensation to achieve reduced bit rates while maintaining perceptual and semantic quality. Our findings show that semantic image synthesis effectively adapts to minute errors resulting from motion estimation, eliminating the need to transmit the residuals. We recommend the Group of Pictures approach as a more efficient alternative. Comparative assessments against HEVC and VVC confirm the method's effectiveness. This research paves the way for efficient real-time semantic video communication, addressing the demands of data-intensive visual applications.

关键词： semantic video communication semantic synthesis video coding

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HYPERSPECTRAL SKIN vision CHALLENGE: CAN YOUR CAMERA SEE BEYOND YOUR SKIN? 49

HYPERSPECTRAL SKIN VISION CHALLENGE: CAN YOUR CAMERA SEE BEY...

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Ng, Pai Chet Chi, Zhixiang Low, Malcolm Lu, Juwei Plataniotis, Konstantinos N. Boulgouris, Nikolaos Bourlai, Thirimachos Ro, Yong Man Singapore Inst Technol Singapore Singapore Univ Toronto Toronto ON Canada Huawei Noahs Ark Lab Singapore Singapore Brunel Univ Uxbridge Middx England Univ Georgia Athens AL USA Korea Adv Inst Sci & Technol Daejeon South Korea

ISBN: (纸本)9798350374520;9798350374513

The ICASSP-SP Grand Challenge on Hyperspectral Skin vision aims to democratize skin analysis by leveraging low-cost consumer-grade cameras to reconstruct vital spectral reflectance data. Addressing the accessibility limitation of costly hyperspectral equipment, this challenge tasks participants with decoding skin spectral information crucial for assessing melanin and hemoglobin concentrations. The provided Hyper-Skin dataset is carefully curated following ethical guidelines, consisting of a total of 306 hyperspectral data from 51 human subjects. Through comprehensive evaluation with Spectral Angle Mapper (SAM), fairness and accuracy in spectral reconstruction methods are ensured, encouraging advancements with real-world applications. This challenge attracted 51 teams and yielding 9 complete submissions. The top 5 teams achieves significant performance with average SAM score of 0.09486. This achievement underscores the transformative potential of this initiative in reshaping skin analysis accessibility and driving interdisciplinary progress with profound societal implications.

关键词： hyperspectral skin vision skin spectral reconstruction

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E2SIFT: NEUROMORPHIC SIFT VIA DIRECT FEATURE PYRAMID RECOVERY FROM EVENTS 31

E2SIFT: NEUROMORPHIC SIFT VIA DIRECT FEATURE PYRAMID RECOVER...

引用

2024 international conference on Image processing

作者： Henry, Chris Maharjan, Paras Li, Zhu York, George Univ Missouri Dept Comp Sci & Elect Engn Kansas City MO 64110 USA US Air Force Acad Acad Ctr UAS Res Colorado Springs CO 80840 USA

ISBN: (纸本)9798350349405;9798350349399

In recent years, event cameras have achieved significant attention due to their advantages over conventional cameras. Event cameras have high dynamic range, no motion blur, and high temporal resolution. Contrary to traditional cameras which generate intensity frames, event cameras output a stream of asynchronous events based on brightness change. There is extensive ongoing research on performing computer vision tasks like object detection, classification, etc via the event camera. However, due to the unconventional output format of the event camera, it is difficult to perform computer vision tasks directly on the event stream. Mostly, works reconstruct the intensity image from the event stream and then perform such tasks. An important and crucial task is feature detection and description. Scale-invariant feature transform (SIFT) is a widely-used scale-invariant keypoint detector and descriptor that is invariant to transformations like scale, rotation, noise, and illumination. In this work, given an event voxel, we directly generate the LoG pyramid for SIFT keypoint detection. We fit a 3rd-degree polynomial and calculate the polynomial roots to compute the scale-space extrema response for SIFT keypoint detection. Since the extrema computation is performed after LoG thresholding, the solution is computationally less expensive. Experimental results validate the effectiveness of our system.

关键词： neuromorphic vision sensor event camera scale-invariant feature transform SIFT keypoint detection

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DIVERSIFYING DEEP ENSEMBLES: A SALIENCY MAP APPROACH FOR ENHANCED OOD DETECTION, CALIBRATION, AND ACCURACY 31

DIVERSIFYING DEEP ENSEMBLES: A SALIENCY MAP APPROACH FOR ENH...

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2024 international conference on Image processing

作者： Dereka, Stanislav Karpukhin, Ivan Zhdanov, Maksim Kolesnikov, Sergey Tinkoff Moscow Russia Moscow Inst Phys & Technol Moscow Russia Natl Univ Sci & Technol MISIS Moscow Russia

ISBN: (纸本)9798350349405;9798350349399

Deep ensembles are capable of achieving state-of-the-art results on classification and out-of-distribution (OOD) detection tasks. However, their effectiveness is limited due to the homogeneity of learned patterns within ensembles. To overcome this issue, our study introduces Saliency-Diversified Deep Ensembles (SDDE1), a novel approach that promotes diversity among ensemble members by leveraging saliency maps. Through incorporating saliency map diversification, our method outperforms conventional ensemble techniques and improves calibration on multiple classification and OOD detection tasks. In particular, the proposed method achieves state-of-the-art OOD detection quality, calibration, and accuracy on multiple benchmarks, including CIFAR10/100 and large-scale ImageNet datasets.

关键词： Ensemble diversity OOD detection calibration computer vision neural networks

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