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Research on Path Planning of Mobile robot by Fusing A∗ and DWA Algorithms 8

Research on Path Planning of Mobile Robot by Fusing A∗ and ...

引用

8th international conference on Intelligent Computing and signal processing, ICSP 2023

作者： Sun, Yunfeng Liu, Jianxiang Kong, Xiangpeng Zhang, Fuxiang Wu, Yulu Li, Ling Shandong Provincial Key Laboratory of Robot and Manufacturing Automation Technology Ji Nan China Shandong Institute for Product Quality Inspection Ji Nan China

ISBN: (纸本)9798350302455

The traditional A∗ algorithm has low search efficiency, many turning points in the planned path, and cannot achieve dynamic path planning when facing unknown obstacles in the environment. This article proposes a fusion algorithm that combines the A∗ algorithm with the Dynamic Window Approach (DWA) algorithm, which uses the DWA algorithm's dynamic window evaluation function to distinguish between known and unknown obstacles. The key points of the A∗ algorithm's planned path are extracted as temporary targets for the DWA algorithm, achieving the fusion of A∗ and DWA algorithms based on global optimality. The experimental results show that the fusion algorithm can ensure global optimality;and avoid unknown obstacles in the environment timely and effectively, achieving dynamic path planning. © 2023 IEEE.

关键词： Motion planning

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A Novel Dual Watermarking for ECG signals with Improved Payload 1

引用

8th international conference on Computer vision and Image processing (CVIP)

作者： Rani, Jyoti Anand, Ashima Shivani, Shivendra Thapar Inst Engn & Technol CSED Patiala Punjab India

ISBN: (数字)9783031581816

ISBN: (纸本)9783031581809;9783031581816

The requirement to safeguard the integrity and validity of ECG signals drives the adoption of watermarking in these signals. Any tampering with or manipulation of ECG signals can result in inaccurate diagnosis or treatment because these signals are crucial for identifying and monitoring cardiovascular illnesses. Also, these signals are frequently sent via the internet, raising the possibility of unwanted access and manipulation. Hence, ECG signal watermarking is crucial for maintaining the reliability and accuracy of these signals in both clinical and research environments. This paper presents a novel ECG signal-based dual watermarking framework using a combination of two medical images: chest X-ray and PET image. A hybrid of DTCWT (Dual-Tree Complex Wavelet Transforms), HD (Hessenberg Decomposition), and MSVD (Multi-resolution singular valued decomposition) is used to embed the dual watermark. This hybrid method represented a significant enhancement not just in aspects of retrieving hidden data from the watermarked ECG signals but also in terms of its resistance to several attacks. To demonstrate the effectiveness of the watermarked ECG signal, we have evaluated the efficacy of the suggested technique using the PSNR, NC, KL, PRD and SSIM parameters. The recovered dual watermark is tested and found to be resistant to various attacks. The simulation results also show that the proposed methodology provided the best results of performance parameters, even when the size of the payload is large.

关键词： ECG signal Dual Watermarking MVMD Pan Tompkins DTCWT MSVD NSCT Hessenberg Decomposition

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vision TRANSFORMER-BASED RETINA VESSEL SEGMENTATION WITH DEEP ADAPTIVE GAMMA CORRECTION 47

VISION TRANSFORMER-BASED RETINA VESSEL SEGMENTATION WITH DEE...

引用

47th IEEE international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Yu, Hyunwoo Shim, Jae-hun Kwak, Jaeho Song, Jou Won Kang, Suk-Ju Sogang Univ Dept Elect Engn Seoul South Korea

ISBN: (纸本)9781665405409

Accurate segmentation of the retina vessel is essential for the early diagnosis of eye-related diseases. Recently, convolutional neural networks have shown remarkable performance in retina vessel segmentation. However, the complexity of edge structural information and the changeable intensity distribution depending on retina images reduce the performance of the segmentation tasks. This paper proposes two novel deep learning-based modules, channel attention vision transformer (CAViT) and deep adaptive gamma correction (DAGC), to tackle these issues. The CAViT jointly applies the efficient channel attention (ECA) and the vision transformer (ViT), in which the channel attention module considers the interdependency among feature channels and the ViT discriminates meaningful edge structures by considering the global context. The DAGC module provides the optimal gamma correction value for each input image by jointly training a CNN model with the segmentation network so that all the retina images are mapped to a unified intensity distribution. The experimental results show that our proposed method achieves superior performance compared to conventional methods on widely used datasets, DRIVE and CHASE DB1.

关键词： vision Transformer Channel Attention Gamma Correction Retina Vessel Segmentation

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Active Learning for Efficient Few-Shot Classification 48

Active Learning for Efficient Few-Shot Classification

引用

48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Abdali, Aymane Gripon, Vincent Drumetz, Lucas Boguslawski, Bartosz Imt Atlantique Umr Cnrs 6285 Lab-STICC BrestF-29238 France Schneider Electric France

ISBN: (纸本)9781728163277

We introduce the problem of Active Few-Shot Classification (AFSC) where the objective is to classify a small, initially unlabeled, dataset given a very restrained labeling budget. This problem can be seen as a rival paradigm to classical Transductive Few-Shot Classification (TFSC), as both these approaches are applicable in similar conditions. We first propose a methodology that combines statistical inference, and an original two-tier active learning strategy that fits well into this framework. We then adapt several standard vision benchmarks from the field of TFSC. Our experiments show the potential benefits of AFSC can be substantial, with gains in average weighted accuracy of up to 10% compared to state-of-the-art TFSC methods for the same labeling budget. We believe this new paradigm could lead to new developments and standards in data-scarce learning settings. © 2023 IEEE.

关键词： Active Learning Classification Few-shot vision

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Path Planning Method of Garbage Cleaning robot Based on Mobile Communication Network 7th

Path Planning Method of Garbage Cleaning Robot Based on Mobi...

引用

7th EAI international conference on Advanced Hybrid Information processing, ADHIP 2023

作者： Tan, Xinyan Lv, Xiaoying Dalian University of Science and Technology Dalian116052 China

ISBN: (纸本)9783031505454

Aiming at many problems brought by the complex running environment, controller performance and obstacles of garbage cleaning robot, this paper puts forward a path planning method of garbage cleaning robot based on mobile communication network. Jud that initial signal rate of the mobile communication network, constructing a motion model of the clean robot, and planning the robot grasping trajectory according to the model;According to the straight path planning and turning path planning, the planning method is studied. The experimental results show that the navigation deviation of the proposed method is small, which can avoid obstacles and effectively plan the path of the garbage cleaning robot. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Motion planning

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Image Generation is May All You Need for VQA 48

Image Generation is May All You Need for VQA

引用

48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Kim, Kyungho Lee, Junseo Lee, Jihwa ActionPower Corporation Korea Republic of

ISBN: (纸本)9781728163277

Visual Question Answering (VQA) stands to benefit from the boost of increasingly sophisticated Pretrained Language Model (PLM) and Computer vision-based models. In particular, many language modality studies have been conducted using image captioning or question generation with the knowledge ground of PLM in terms of data augmentation. However, image generation of VQA has been implemented in a limited way to modify only certain parts of the original image in order to control the quality and uncertainty. In this paper, to address this gap, we propose a method that utilizes the diffusion model, pre-trained with various tasks and images, to inject the prior knowledge base into generated images and secure diversity without losing generality about the answer. In addition, we design an effective training strategy by considering the difficulty of questions to address the multiple images per QA pair and to compensate for the weakness of the diffusion model. VQA model trained on our strategy improves significant performance on the dataset that requires factual knowledge without any knowledge information in language modality. © 2023 IEEE.

关键词： Computer vision

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A Three-Stage Low-Illumination Image Enhancement Method Based on Feature Refining and Its Application in Inspection robot for High-Voltage Substation Room 8

A Three-Stage Low-Illumination Image Enhancement Method Base...

引用

8th IEEE international conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Fu, Bo Wang, Hongguang Jiang, Yong Song, Yifeng Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350300178

To address color deviation and noise problem in some Retinex theory based image enhancement methods, this paper proposes a three-stage low-illumination image enhancement method based on feature refining. Additionally, a vision subsystem for an electric inspection robot is introduced based on this network to mitigate the impact of low illumination environments on vision detection tasks in high-voltage substation rooms. In the first stage, the proposed network decomposes the image using Retinex theory and leverages the Swin Transformer to perceive global information. In the second stage, the image undergoes preliminary enhancement. In the third stage, the feature refining network is introduced. Initially, a U-shaped network is employed to extract image features. Subsequently, a convolutional neural network and attention mechanism are applied to screen the extracted information, completing the feature refinement and improving the quality of the result. Through illumination assessment and algorithm selection, the proposed vision subsystem for the robot effectively addresses the challenges of low illumination enhancement and object detection in complex lighting conditions in high-voltage transformer rooms. Experimental results demonstrate that the proposed network outperforms some state-of-the-art methods in terms of peak signal-to-noise ratio and structural similarity index. Moreover, the vision subsystem presented in this paper significantly enhances the robot's detection capabilities, reducing the omission ratio and fallout ratio, thus validating the effectiveness of the proposed method. © 2023 IEEE.

关键词： Image enhancement

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Energy Efficient 2D FIR Filter and Multiplier Design for Image processing Applications

Energy Efficient 2D FIR Filter and Multiplier Design for Ima...

引用

2024 IEEE international conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Reddy, C. Venkata Srikanth Sindhu, B. Deepak, A.G.M. Preetham, D.V.S. Prasad, T.V.S. Gowtham Electronics and Communication Engineering Tirupati India Tirupati India Tirupati India

ISBN: (纸本)9798350382693

The 2D FIR filters are simple to design which are more frequently used many more real world applications. The image processing application like medical diagnosis, pattern recognition and robot vision. This paper introduces an energy-efficient 2D Finite Impulse Response (FIR) filter design for image processing tasks like image denoising, image enhancing, image restoration etc., The 2D FIR filter is designed using transpose direct form architecture by 3x3, 5x5 and 7x7 Kernal mapping. The multiplier in this filter is replaced with the multiplier is designed using Booth-Dadda technique (which reduces number of partial products and number of additions operations). The multiplier is designed using 4:2 compressor to reduce power consumption and delay. Xilinx ISE 14.7 software with Spartan3E XC3S100E device is utilized to implement the filter in Verilog HDL and to verify the design parameters of the filter. © 2024 IEEE.

关键词： FIR filters

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AirTrack: Onboard Deep Learning Framework for Long-Range Aircraft Detection and Tracking

AirTrack: Onboard Deep Learning Framework for Long-Range Air...

引用

IEEE international conference on robotics and Automation (ICRA)

作者： Ghosh, Sourish Patrikar, Jay Moon, Brady Hamidi, Milad Moghassem Scherer, Sebastian Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9798350323658

Detect-and-Avoid (DAA) capabilities are critical for safe operations of unmanned aircraft systems (UAS). This paper introduces, AirTrack, a real-time vision-only detect and tracking framework that respects the size, weight, and power (SWaP) constraints of sUAS systems. Given the low signal-to-Noise ratios (SNR) of far away aircraft, we propose using full resolution images in a deep learning framework that aligns successive images to remove ego-motion. The aligned images are then used downstream in cascaded primary and secondary classifiers to improve detection and tracking performance on multiple metrics. We show that AirTrack outperforms state-of-the art baselines on the Amazon Airborne Object Tracking (AOT) Dataset. Multiple real world flight tests with a Cessna 182 interacting with general aviation traffic and additional near-collision flight tests with a Bell helicopter flying towards a UAS in a controlled setting showcase that the proposed approach satisfies the newly introduced ASTM F3442/F3442M standard for DAA. Empirical evaluations show that our system has a probability of track of more than 95% up to a range of 700m. [Video](1)

关键词： Aircraft detection

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Research on image optimization of graphic design based on 3D laser vision technology 2

Research on image optimization of graphic design based on 3D...

引用

2nd international conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Yang, Dianqing Liu, Renjing Visual Design College Keimyung University Dalseo-gu Daegu704-701 Korea Republic of

ISBN: (纸本)9781510689053

To prevent image distortion, this paper explores methods for enhancing and optimizing graphic design images using 3D laser vision technology. The process involves collecting graphic design image data, mapping 3D laser information onto the surface of the image to form an information map, and utilizing this data for locally weighted complexity processing. A histogram of the graphic design image is constructed, followed by scanning and grayscale transformation to eliminate noise. The image histogram is then segmented using a block-based local enhancement method to achieve the optimization and enhancement of the graphic design image. Experimental results show that under different noise standard deviations, the average peak signal-to-noise ratio (PSNR) of the proposed method is 36.62 dB, and the average structural similarity index (SSIM) is 0.9526. This method effectively reduces noise and enhances the visual quality of graphic design images, improving the ability of the human eye to discriminate information in these images. © 2025 SPIE.

关键词： Image enhancement

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