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检索条件"任意字段=International Conference on Robot Vision and Signal Processing"

共 17893 条记录，以下是311-320 订阅

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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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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...

引用

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

引用

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...

引用

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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A wheelchair differential control method based on the coupling of control signal and environmental information 21

A wheelchair differential control method based on the coupli...

引用

21st IEEE international conference on Mechatronics and Automation (IEEE ICMA)

作者： Qi, Kaicheng Li, Chao Yin, Zhiyang Zhang, Jianjun Guo, Shijie Shan, Xinying Hebei Univ Technol Dept Mech Engn 5340 Xiping Rd Tianjin 300401 Peoples R China Natl Rehabil AIDS Res Ctr Dept Rehabil Engn 1 Ronghua Middle Rd Beijing 100176 Peoples R China

ISBN: (纸本)9798350388084;9798350388077

We propose a wheelchair differential speed control method based on the coupling of control signals and environmental information, which firstly determines the motion state of the wheelchair based on the displacement offset, so as to generate the corresponding control signals;then ultrasound, vision and IMU sensors are used to collect distance, image and angle information respectively, and the environmental information is fused based on fuzzy control to get the integrated environmental factor;Finally, the control signals and Integrated environmental factor are coupled to calculate the expected speeds of the left and right wheels under different motion states. The method fully reflects the environmental information and realizes the full coupling between the control signal and the environmental information, establishes the differential speed model of the wheelchair considering the environmental information, ensures the safety and reliability of the wheelchair during operation, and realizes the intelligent control of the wheelchair.

关键词： Control signal Information fusion Fuzzy control Integrated environmental factor Differential model

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ADAPTXRAY: vision TRANSFORMER AND ADAPTER IN X-RAY IMAGES FOR PROHIBITED ITEMS DETECTION 31

ADAPTXRAY: VISION TRANSFORMER AND ADAPTER IN X-RAY IMAGES FO...

引用

2024 international conference on Image processing

作者： Huang, Yaobin Gao, Hongxia Li, Xiaomeng South China Univ Technol Guangzhou Peoples R China Pazhou Lab Guangzhou Peoples R China

ISBN: (纸本)9798350349405;9798350349399

Prohibited items detection refers to the non-contact inspection of passenger baggage for potential threats through X-ray image. Since the uncertainty of artificial security screening, previous research has mainly concentrated on direct transfer by universal detection frameworks based on natural image and design in enhance or aware module with salient features like edge and color. With the increasing complexity in both categories and quantities of X-ray security inspection, the unreliability of direct transfer and complication of taskspecific design make the existing algorithms difficult to reliably and efficiently adapt the complex security inspection. To address this challenge, we propose the Adapter in X-ray (AdaptXray), which firstly explores pre-trained vision Transformer with powerful representation and Parameter Efficient Transfer Learning method applying for prohibited items detection. Specifically, we design Color Prior Extractor to perceive local prior features from different color spaces. Subsequently, we develop Global-aware Self-Adapter to adaptively perceive and optimize the global universal features in the backbone. Additionally, we propose Local-aware Interactive Adapter to incorporate prior knowledge into the pretrained backbone. Thorough experimentation on two public baggage datasets, namely OPIXray and PIDray, demonstrates that the effectiveness of our proposed method, outperforming the existing renown CNN-based detection approaches.

关键词： Prohibited items detection X-ray image Deep learning vision Transformer Parameter Efficient Transfer Learning

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vision Transformer MST++: Efficient Hyperspectral Skin Reconstruction 49

Vision Transformer MST++: Efficient Hyperspectral Skin Recon...

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2024 IEEE international conference on Acoustics, Speech, and signal processing Workshops, ICASSPW 2024

作者： Silveira, Ana Clara C. Do Carmo, Diedre S. Ueda, Lucas H. Fantinato, Denis G. Costa, Paula D. P. Rittner, Leticia Brazil Cpqd Brazil Artificial Intelligence Lab. Recod.ai Institute of Computing Unicamp Brazil

ISBN: (纸本)9798350374513

Channel reconstruction transforms a subsampled multispectral image into hyperspectral, offering hyperspectral imaging benefits without a dedicated camera. MST++ is a state of the art channel reconstruction technique, but it faces memory limitations for high spatial resolution images. In this context, we introduce VITMST++, a novel architecture incorporating vision Transformer embedding and compression, multi-resolution image context and a channel-weighted loss. Developed for the ICASSP 2024 Hyperspectral Skin Challenge, VITMST++ outperforms the state-of-the-art MST++ in both performance and computational efficiency in channel reconstruction. © 2024 IEEE.

关键词： Image reconstruction

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