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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition"

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Path Planning Model of Intelligent Robot based on computer vision recognition Algorithm 6

Path Planning Model of Intelligent Robot based on Computer V...

引用

6th International conference on Inventive Computation Technologies, ICICT 2023

作者： Zhang, Xiaolei Zhang, Xiaotao Guangdong Country Garden Polytechnic Guangdong Qingyuan China China Australia Business College of Shanxi Shanxi Jinzhong China

ISBN: (纸本)9798350398496

This study has designed a path planning model for intelligent robot based on computer vision recognition algorithm. Here, the redundant nodes present in the pre-planned path are removed through the node screening mechanism, and the later the artificial potential field method is introduced to ensure that a safe distance is always maintained from the unknown obstacles present in the re-planning process. At the same time, this research study adopts the method of setting virtual target points to solve the local extreme value problem that may be encountered in the actual movement of the machine. For developing an efficient and intelligent path planning model, the computer vision should be referred The binocular recognition is equipped with two symmetrical signal acquisition cameras, which can realize the positioning of the status information. The enhanced theoretical vision algorithm is then combined for performing systematic optimization. The performance is validated by testing it on different datasets. © 2023 ieee.

关键词： Motion planning

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Quantum Permutation Synchronization

Quantum Permutation Synchronization

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Birdal, Tolga Golyanik, Vladislav Theobalt, Christian Guibas, Leonidas Stanford Univ Stanford CA 94305 USA Max Planck Inst Informat SIC Saarbrucken Germany

ISBN: (纸本)9781665445092

We present QuantumSync, the first quantum algorithm for solving a synchronization problem in the context of computer vision. In particular, we focus on permutation synchronization which involves solving a non-convex optimization problem in discrete variables. We start by formulating synchronization into a quadratic unconstrained binary optimization problem (QUBO). While such formulation respects the binary nature of the problem, ensuring that the result is a set of permutations requires extra care. Hence, we: (i) show how to insert permutation constraints into a QUBO problem and (ii) solve the constrained QUBO problem on the current generation of the adiabatic quantum computers D-Wave. Thanks to the quantum annealing, we guarantee global optimality with high probability while sampling the energy landscape to yield confidence estimates. Our proofof-concepts realization on the adiabatic D-Wave computer demonstrates that quantum machines offer a promising way to solve the prevalent yet difficult synchronization problems.

关键词： computer vision Quantum algorithm Adiabatic Hardware pattern recognition Synchronization Optimization

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The Virtual Air Canvas Using Image Processing

The Virtual Air Canvas Using Image Processing

引用

2023 International conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Pavithra, K. Geetha, A. Chinnaiyan, R. Alliance University Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350317060

One of the most interesting and challenging research focuses on pattern recognition and image processing has emerged in recent days is writing in the air. In many different applications, it can improve the interface between a machine and a human and offers a substantial contribution to the development of automated operations. In the field of computer vision, object tracking is considered a key challenge. The method of analyzing a video usually consists of three primary steps: recognizing the object, tracking its movement from frame to frame, and finally evaluating its behavior. Choosing an adequate object representation, selecting tracking features, identifying objects, and tracking them are the four problems taken into consideration for object tracking. Object tracking algorithms are widely used in many real-world applications, including autonomous surveillance, video indexing, and vehicle navigation. This work exploits this gap by developing a motion-to-text converter that may be used as software for wearable intelligent devices that allow writing in the air. The proposed work acts as a recorder of rare gestures. computer vision will be utilized to track the finger's path. With the generated text, messages, emails, and other kinds of correspondence can all be sent. It will enable effective communication for the deaf. Keywords - object, emoji's, image color, camera © 2023 ieee.

关键词： computer vision

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Gaze Estimation using Transformer 26

Gaze Estimation using Transformer

引用

26th International conference on pattern recognition / 8th International Workshop on Image Mining - Theory and Applications (IMTA)

作者： Cheng, Yihua Lu, Feng Beihang Univ Beijing Peoples R China Peng Cheng Lab Shenzhen Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Recent work has proven the effectiveness of transformers in many computer vision tasks. However, the performance of transformers in gaze estimation is still unexplored. In this paper, we employ transformers and assess their effectiveness for gaze estimation. We consider two forms of vision transformer which are pure transformers and hybrid transformers. We first follow the popular ViT and employ a pure transformer to estimate gaze from images. On the other hand, we preserve the convolutional layers and integrate CNNs as well as transformers. The transformer serves as a component to complement CNNs. We compare the performance of the two transformers in gaze estimation. The Hybrid transformer significantly outperforms the pure transformer in all evaluation datasets with fewer parameters. We further conduct experiments to assess the effectiveness of the hybrid transformer and explore the advantage of the self-attention mechanism. Experiments show the hybrid transformer can achieve state-of-the-art performance in all benchmarks with pre-training. To facilitate further research, we release codes and models in https://***/yihuacheng/GazeTR.

关键词： Convolutional codes computer vision Costs Estimation Benchmark testing Transformers Distance measurement

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Design of Active Collision Avoidance Algorithm for Driverless Cars Based on Machine vision 6

Design of Active Collision Avoidance Algorithm for Driverles...

引用

2023 ieee 6th International conference on Information Systems and computer Aided Education, ICISCAE 2023

作者： Hu, Xinyuan Ye, Naijia University of Sussex BrightonBN1 9RH United Kingdom

ISBN: (纸本)9798350313444

With the continuous progress of society, the problem of traffic congestion is becoming increasingly serious. However, when an unmanned vehicle is driving on the highway, it is unavoidable to encounter situations such as vehicle collisions and rear-end collisions. In order to effectively solve this problem, this article proposes to use machine vision technology to deal with such events. By using a computer image recognition system, the required recognition information can be analyzed and extracted to obtain the required results. At the same time, the video data also needs to be converted into digital signals and output to the control unit to realize the automatic collision avoidance function. This article tests the performance of the active collision avoidance algorithm of driverless cars. The test results show that the recall rate of the collision avoidance algorithm is between 0.7-0.89, and the highest collision avoidance accuracy can reach 0.97. This shows that this method can greatly improve the safety performance of driverless cars and create a safer and more convenient travel environment. © 2023 ieee.

关键词： Active Collision Avoidance Automobile Design Driverless Driving Machine vision

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YOLOv7-ConvTrans: Hybrid vision Transformer with YOLOv7 for Underwater Object Detection 4

YOLOv7-ConvTrans: Hybrid Vision Transformer with YOLOv7 for ...

引用

4th ieee International conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Delsey, M.J. Bibal Benifa, J.V. Indian Institute of Information Technology Department of Computer Science and Engineering Kottayam India

ISBN: (数字)9798331528348

ISBN: (纸本)9798350352931

Underwater object detection plays a significant role in marine exploration activities such as ecological monitoring, conservation of undersea ecosystems, and underwater robotics. In contrast to detection in the atmosphere on land, underwater detection is challenging due to color distortion and attenuation, which render the detection process more difficult and imprecise. To address these issues, this paper proposes an improved detection framework, YOLOv7-ConvTrans. The YOLOv7 architecture is optimized by integrating a convolution vision transformer in the neck region to enhance the detection accuracy of small and occluded objects. The proposed method reduces redundancy, computational cost, and recognition time to extract significant feature maps from the imagery. In the experimental assessment on the URPC2019 dataset, a mAP of 80.39 and on the Brackish dataset, 92.61, indicate high detection accuracy. Finally, our proposed approach provides a valuable framework for designing underwater vision systems that can be utilized in various scientific and exploratory domains. © 2024 ieee.

关键词： Machine vision

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Feedback control of event cameras

Feedback control of event cameras

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Delbruck, Tobi Graca, Rui Paluch, Marcin UZH ETH Zurich Inst Neuroinformat Zurich Switzerland

ISBN: (纸本)9781665448994

Dynamic vision sensor event cameras produce a variable data rate stream of brightness change events. Event production at the pixel level is controlled by threshold, bandwidth, and refractory period bias current parameter settings. Biases must be adjusted to match application requirements and the optimal settings depend on many factors. As a first step towards automatic control of biases, this paper proposes fixed-step feedback controllers that use measurements of event rate and noise. The controllers regulate the event rate within an acceptable range using threshold and refractory period control, and regulate noise using bandwidth control. Experiments demonstrate model validity and feedback control.

关键词： computer vision Current measurement conferences Bandwidth Production vision sensors Cameras

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recognition pattern Analysis of Astronomical Object Forms Using the Analytical Model 14

Recognition Pattern Analysis of Astronomical Object Forms Us...

引用

14th International conference on Advanced computer Information Technologies, ACIT 2024

作者： Khlamov, Sergii Savanevych, Vadym Troianskyi, Volodymyr Grebennik, Igor Bondar, Yehor Netrebin, Yuriy Kharkiv National University of Radio Electronics Department of Systems Engineering Kharkiv Ukraine Astronomical Institute of the Slovak Academy of Sciences Tatranska Lomnica Slovakia

ISBN: (纸本)9798350350036

Image processing and pattern recognition in astronomy represents a dynamic field of study where the analysis of astronomical object shapes plays a crucial role. This is associated with the necessity of identifying and classifying various patterns present in astronomical images. An important aspect of processing astronomical images is the recognition and analysis of patterns contained within these images. patterns can vary from circular shapes of stars and galaxies to elongated structures of gas clouds. Understanding these patterns not only helps us identify objects in space but also provides unique information about their structure, evolution, and physical characteristics. Another key aspect is the utilization of an analytical image model. This is a mathematical approach that allows modeling images of objects in space and analyzing their characteristics. The analytical model enables the detection of brightness peaks in images, determining typical object shapes, and conducting various analytical investigations. © 2024 ieee.

关键词： Object detection

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Context Unaware Knowledge Distillation for Image Retrieval 1

引用

International conference on computer vision and Machine Intelligence, CVMI 2022

作者： Reddy, Bytasandram Yaswanth Dubey, Shiv Ram Sanodiya, Rakesh Kumar Karn, Ravi Ranjan Prasad Department of Computer Science and Engineering Indian Institute of Information Technology Sri City Chittoor India Computer Vision and Biometrics Laboratory Indian Institute of Information Technology Allahabad India

ISBN: (数字)9789811978678

ISBN: (纸本)9789811978661

Existing data-dependent hashing methods use large backbone networks with millions of parameters and are computationally complex. Existing knowledge distillation methods use logits and other features of the deep (teacher) model and as knowledge for the compact (student) model, which requires the teacher’s network to be fine-tuned on the context in parallel with the student model on the context. Training teacher on the target context requires more time and computational resources. In this paper, we propose context unaware knowledge distillation that uses the knowledge of the teacher model without fine-tuning it on the target context. We also propose a new efficient student model architecture for knowledge distillation. The proposed approach follows a two-step process. The first step involves pre-training the student model with the help of context unaware knowledge distillation from the teacher model. The second step involves fine-tuning the student model on the context of image retrieval. In order to show the efficacy of the proposed approach, we compare the retrieval results, no. of parameters, and no. of operations of the student models with the teacher models under different retrieval frameworks, including deep cauchy hashing (DCH) and central similarity quantization (CSQ). The experimental results confirm that the proposed approach provides a promising trade-off between the retrieval results and efficiency. The code used in this paper is released publicly at https://***/satoru2001/CUKDFIR. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Distillation

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Voiced Subordinate for Visually Impaired in record maintenance with Proximal Object recognition and Voice Assistant Framework 3

Voiced Subordinate for Visually Impaired in record maintenan...

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3rd International conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Sajini, S. Pushpa, B. Annamalai University Faculty of Science Department of Computer and Information Science Tamil Nadu Chidambaram India

ISBN: (纸本)9781665494007

Proximal Object detection using computer vision is one of the important domains that comprehends the users or objects in front of them through vision Glasses to recognise objects and inform the Visually Impaired (VI). The major objective of the research was to design a Proximal Object recognition and Voice Assistant Framework (PORVAF) that detects the object with plots and recognises the objects using the COCO dataset that shares global database for recognising objects. The recognised objects were further tested for proximity and analysed for the percentage of accuracy of detecting the object using computer vision Techniques. Along with the percentage, the date and time of the recognition of objects were recorded and stored in the local database and sent as voice output for the visually impaired user. This framework outperformed the benchmark models by achieving high accuracy of proximality object detection. The significance of the work is to assist the VI in office record maintenance and to remove unemployability for VI people in the world. © 2023 ieee.

关键词： Object recognition

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