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

共 18124 条记录，以下是241-250 订阅

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Effects of Gabor filters on classification performance of CNNs trained on a limited number of conditions

Effects of Gabor filters on classification performance of CN...

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international Technical conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)

作者： Morita, Akito Okuno, Hirotsugu Osaka Inst Technol Grad Sch Informat Sci & Technol Osaka Japan Osaka Inst Technol Fac Informat Sci & Technol Osaka Japan

ISBN: (纸本)9798350379068;9798350379051

In this study, we propose a technique to improve the accuracy and reduce the size of convolutional neural networks (CNNs) running on edge devices for real-world robot vision applications. CNNs running on edge devices must have a small architecture, and CNNs for robot vision applications involving on-site object recognition must be able to be trained efficiently to identify specific visual targets from data obtained under a limited variation of conditions. The visual nervous system (VNS) is a good example that meets the above requirements because it learns from few visual experiences. Therefore, we used a Gabor filter, a model of the feature extractor of the VNS, as a preprocessor for CNNs to investigate the accuracy of the CNNs trained with small amounts of data. To evaluate how well CNNs trained on image data acquired under a limited variation of conditions generalize to data acquired under other conditions, we created an image dataset consisting of images acquired from different camera positions, and investigated the accuracy of the CNNs that trained using images acquired at a certain distance. The results were compared after training on multiple CNN architectures with and without Gabor filters as preprocessing. The results showed that preprocessing with Gabor filters improves the generalization performance of CNNs and contributes to reducing the size of CNNs.

关键词： CNN Neural network Gabor neuro-inpired image processing image classification

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Design of robot vision Recognition System

Design of Robot Vision Recognition System

引用

international conference on Image processing, Computer vision and Machine Learning (ICICML)

作者： Wen, Binbin Wang, Yifan Xue, Yuming Tianjin Univ Technol Sch Integrated Circuit Sci & Engn Tianjin Peoples R China

In this paper, a robot vision recognition system is developed based on the robot Operating System (ROS) and the Open Source Computer vision (Open CV), which mainly implements face recognition, object detection, motion... 详细信息

ISBN: (纸本)9781665464680

关键词： Face recognition Edge detection Motion analysis

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Development of an Intelligent robotized Machine vision Automated System for Bacterial Growth Monitoring

Development of an Intelligent Robotized Machine Vision Autom...

引用

2023 international conference on signal processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2023

作者： Ramanathan, Prabhu Ericsson, Mikael University West Department of Engineering Science Trollhättan Sweden

ISBN: (纸本)9798350312126

Pathogenic bacterial growth detection and monitoring is an important scientific process in the field of quality control in the food, water, and medical industries. Very-large-scale process of such bacteria growth monitoring is possible only with an automated process. The mechanism must make sure that the sample is continuously monitored, and detected, data is communicated to supervisors and managers, and data is stored historically retrievable for quality control and analysis. A manual bacteria inspection among the Petri dishes incubated of such bacterial growth in food processing was attempted for automation. The manual inspection in a microbiological industry involves;an operator inspecting the input petri discs to check if there are bacteria, writing down the barcode of the corresponding petri dish, and then sorting the Petri discs depending on the bacterial growth. In this automation attempt of automatizing this petri-disc inspection, the project was split into two phases. 1. Building a vision system to detect bacteria, developing of an algorithm to quantify the growth, and registering the barcode in a registry. 2. The second phase is to design a robot system with programming and define the layout of the station. The development of an intelligent robotized machine vision automated system proves the concept of a major industrial practice that has the potential to significantly increase the quality and productivity of bacterial growth, with increased throughput. © 2023 IEEE.

关键词： Computer vision

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Deep Learning Approaches for Dermoscopic Image-Based Skin Cancer Diagnosis 7

Deep Learning Approaches for Dermoscopic Image-Based Skin Ca...

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IEEE 7th international conference on Advanced Technologies, signal and Image processing (ATSIP)

作者： Elbedoui, Khouloud Mzoughi, Hiba Ben Slima, Mohamed Sfax Univ Natl Sch Elect & Telecommun Sfax Sfax Tunisia Gabes Univ Natl Engn Sch Gabes Gabes Tunisia UR ATISP Sfax Tunisia

ISBN: (纸本)9798350351491;9798350351484

In recent years, due to UV human exposure, the number of skin cancers 'subjects' cases have been increased, therefore, the accurate detection of malign skin cancer at early stage is considered as very crucial for patients' therapy and to increase the survival rates. Melanomas is considered as the most frequent and dangerous type of skin cancer. Even a huge number of deep-learning (DL) and Machine Learning (ML) based-classification methods have been introduced in the literature, there have been suspected cases during the clinical diagnosis of malignant lesions. This paper investigates and explores various DL-based models for an accurate diagnosis and detection of malign and benign skin lesions. Basically, Transfer learning (TL) techniques are adapted to efficient and accurate pre-trained models, mainly EfficientNet-B0-V2 and vision Transformers ViT-b16, on the image-Net datasets. Furthermore, a modified Convolutional Neural Network (CNN) model have been adopted and trained from scratch. A publicly available benchmark dataset has been used in order to evaluate the proposed models 'performances and to compare their effectiveness with state-of-the-arts exiting methods. The obtained results are respectively 79,70%, 86,52%, and 86.97% respectively for CNN, EfficientNet-B0-V2, and ViT-b16 models. The experiments have revealed the effectiveness of our proposed models compared to exiting DL and ML models for classification into benign and malignant skin lesions.

关键词： Melanoma deep learning vision transformers Skin cancer classification CNN

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Research on dual arm collaborative motion control of LNG loading station inspection robot 4

Research on dual arm collaborative motion control of LNG loa...

引用

4th international conference on Advanced Algorithms and signal Image processing, AASIP 2024

作者： Zhang, Qi Gu, Shuguang Li, Lei Fang, Lingfei JARI Automation Co. Ltd. China No. 16 Yunqiao Road Lianyungang China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

With the promotion and application of LNG loading skid automatic control technology and information management technology, LNG loading stations are gradually developing towards unmanned stations. In the unmanned stations, in addition to automation equipment, inspection robots used for station inspection and maintenance are also essential. This article focuses on the research of dual arm inspection robots for unmanned stations, and conducts research on the coordinated motion control of dual arms for inspection robots in loading stations. Firstly, perform D-H parameter kinematic modeling on the designed robot;Secondly, design kinematic solving algorithms and dual arm collaborative motion algorithms based on the D-H model;Finally, a simulation platform is built in the ROS robot system for gripping simulation testing to verify the feasibility of the algorithm. © 2024 SPIE.

关键词： Inspection

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A NEEDLE IN A (MEDICAL) HAYSTACK: DETECTING A BIOPSY NEEDLE IN ULTRASOUND IMAGES USING vision TRANSFORMERS 31

A NEEDLE IN A (MEDICAL) HAYSTACK: DETECTING A BIOPSY NEEDLE ...

引用

2024 international conference on Image processing

作者： Wijata, Agata M. Pycinski, Bartlomiej Nalepa, Jakub Silesian Tech Univ Akad 2A PL-44100 Gliwice Poland Maria Sklodowska Curie Natl Res Inst Oncol Gliwice Branch Tumor Pathol Dept Wybrzeze Armii Krajowej 15 PL-44102 Gliwice Poland

ISBN: (纸本)9798350349405;9798350349399

Needle localization in ultrasound images is pivotal for the successful execution of ultrasound-guided core needle biopsies. Automating the needle detection process can decrease the procedure time and lead to a more precise diagnosis. In this article, we introduce an automatic method for detecting the core needle and determining its trajectory in 2D ultrasound images. In our approach, the vision Transformer architecture, renowned for its self-attention mechanisms is used for needle detection and segmentation, and is followed by the analysis of the Radon transformed segmentation mask to identify the needle's trajectory. The experiments, performed over two clinical datasets of more than 600 ultrasound images rigorously split into various training-test subsets and backed up with a variety of statistical analyses revealed that our approach offers high-quality needle segmentation, and significantly outperforms other techniques in identifying the needle's trajectory, with the trajectory localization errors reduced up to more than 5x when compared to the most competitive deep learning algorithm. We believe that our work may pave the way for more accurate and efficient ultrasound-guided procedures, ultimately improving patient outcomes.

关键词： Core needle biopsy cancer machine learning deep learning vision transformer ultrasound imaging

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VIDEO CLASS-INCREMENTAL LEARNING WITH CLIP BASED TRANSFORMER 31

VIDEO CLASS-INCREMENTAL LEARNING WITH CLIP BASED TRANSFORMER

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2024 international conference on Image processing

作者： Lu, Shuyun Jiao, Jian Wang, Lanxiao Qiu, Heqian Lin, Xingtao Mei, Hefei Li, Hongliang Univ Elect Sci & Technol China Chengdu Peoples R China

ISBN: (纸本)9798350349405;9798350349399

vision Language Pre-training Models have shown significant potential in various domains, but there are few attempts to introduce it in the field of continual learning for video action recognition. We propose Video Class-Incremental Learner with CLIP based Transformer (VCIL-CT), which uses CLIP based vision transformer to train action recognition task by class-incremental learning pipeline. To specifically address the issue of catastrophic forgetting in transformer, we introduce Attention Distillation, which distilling the attention feature from each transformer decoder. In the process of incremental learning of classes, there may be a problem of high bias towards new classes, we incorporate Class Balance Module to prevent bias on new task. Furthermore, we adopt Exemplar Augment strategy to improve exemplar quality on data replay step. We evaluate our proposed method based on the incremental action recognition benchmark presented by TCD, using UCF101, HMDB51, and UESTC-MMEA-CL datasets, and demonstrate the effectiveness of our algorithm compared to existing state-of-the-art continuous learning methods for action recognition.

关键词： class-incremental learning action recognition vision language pre-training attention distillation exemplar augment

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Study of a Condition Monitoring Method Based on the Concept of Complex Fuzzy Sets 20

Study of a Condition Monitoring Method Based on the Concept ...

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IEEE 20th international conference on Automation Science and Engineering (CASE)

作者： de Oliveira, Wesley R. Aeronaut Inst Technol ITA Dept Mechatron Div Mech Engn BR-12228900 Sao Jose Dos Campos SP Brazil

ISBN: (纸本)9798350358513;9798350358520

This paper presents an application of the Complex Fuzzy Set (CFS) concept to the adaptation of an automated condition monitoring method (CMM). It is founded on the previous work from Ramot, which introduced the core aspects of the CFS and defined a related technique for measuring the similarity between two signals. The technique is adapted to the important problem of predicting the health of a system or machine. Some analyses based on synthetic signals are performed to theoretically support main aspects of the method. Other results focus on the use of synthetic signals from a robot model to monitor robot joint degradation, showing the potential of the CMM for different industrial applications that could benefit from a soft online condition monitoring approach.

关键词： Complex Fuzzy Set Condition Monitoring Systems signal processing robot Joint Degradation.

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HYBRID SINGLE INPUT AND MULTIPLE OUTPUT METHOD FOR COMPRESSING FEATURES TOWARDS MACHINE vision TASKS 31

HYBRID SINGLE INPUT AND MULTIPLE OUTPUT METHOD FOR COMPRESSI...

引用

2024 international conference on Image processing

作者： Zhang, Zifu Li, Shengxi Liu, Tie Xu, Mai Xu, Tao Guan, Zhenyu Lv, Zhuoyi Beihang Univ Beijing Peoples R China Vivo Mobile Commun Co Ltd Beijing Peoples R China

ISBN: (纸本)9798350349405;9798350349399

With the advance of deep learning in the BigData era, image/video coding for machines (VCM) as called for proposals by the moving picture experts group (MPEG) now becomes the pivotal technique for extensive intelligent vision tasks. However, existing VCM methods typically focus on compressing features independently at each scale, ignoring the redundancy of features across multiple scales. This paper thus introduces a simple yet effective architecture called hybrid single input and multiple output (H-SIMO) for VCM, which can significantly reduce the redundancy across scales of features. More specifically, as the pyramid structure is commonly employed for localising multi-scale objects, our HSIMO method proposes to compress all features by inputting a single-scale feature while retaining the ability to decompress all the features. Moreover, an entropy model is seamlessly integrated into the training process to efficiently reduce the statistical redundancy of features. During the testing phase, the hybrid coding method, in conjunction with the versatile video coding (VVC), is employed to compress the features from both images and videos. We comprehensively evaluate the performance of our H-SIMO method in two standard machine vision tasks: object detection and instance segmentation, in which the experimental results verify the superior performances of our H-SIMO method.

关键词： Video coding for machines feature compression image compression

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Engineering Applications based on Industrial robots and Machine vision

Engineering Applications based on Industrial Robots and Mach...

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international conference on Image processing, Computer vision and Machine Learning (ICICML)

作者： Huang, Yiren Hao, Weidong Wang, Zhihao Wu, Hao Guilin Univ Elect Technol Sch Mech & Elect Engn Guilin Guangxi Peoples R China

ISBN: (纸本)9781665464680

This paper introduces the structure and operation mode of automatic production line based on the actual situation of laser quenching automatic production line of tool in enterprises. robot vision integrates workpiece positioning coordinates with robot coordinates to realize the positioning and grasping function of robot through machine vision. Focus on OpenCV image processing methods. This paper describes its principle and possible problems from the aspects of system structure, robot coordinate calibration, visual identification and positioning and software design.

关键词： robot machine vision workpiece positioning automation

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