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检索条件"任意字段=2024 Conference on Visual Communications and Image Processing"

共 6921 条记录，以下是121-130 订阅

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Research on interactive virtual assembly technology for agricultural machinery components based on OpenPose

Research on interactive virtual assembly technology for agri...

引用

2024 International conference on Optical and Photonic Engineering, icOPEN 2024

作者： Cai, Xiaona Zeng, Zeqin Zhang, Po Chen, Youbin Huang, Yijie Wang, Hongjun Luo, Zewen Liu, Hanyu GuangDong Polytechnic of Industryand Commerce 1098 Guangzhou Avenue North Xinghua Street Guangzhou China South China Agricultural University 483 Wushan Road Guangzhou China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

In order to enhance the precision and efficiency of the assembly process for intelligent agricultural equipment, this paper integrates machine vision perception and deep learning algorithms, and proposes an OpenPose-based virtual assembly method for key components of equipment. This marks the inaugural instance of employing a binocular stereo vision system in conjunction with the Multiview Bootstrapping algorithm in OpenPose to address the challenges of hand positioning and occlusion during the assembly process. This approach enables the precise detection of hand key points and the accurate calculation of hand position information. To address the high cost of production of physical agricultural equipment, a digital twin model of agricultural equipment components and a virtual hand model are constructed. A virtual assembly platform is then constructed and applied to verify the visual system and conduct interactive virtual assembly tests. The results demonstrate that the platform can rapidly and accurately track the key points of the hand, thereby enabling the interactive virtual assembly of key components of agricultural machinery. © 2025 SPIE.

关键词： Stereo image processing

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Educational images Colour and Memory Retention Conceptual Framework: A Review of Related Literature Conceptualizing Memory Retention of Educational images based on its Color 24

Educational Images Colour and Memory Retention Conceptual Fr...

引用

7th International conference on Educational Technology Management, ICETM 2024

作者： Ainooson-Noonoo, Daniel Kweku Khedkar, Pallavi Parul Institute of Enginering and Technology Parul University Gujarat Vadadora India Department of Mathematics and ICT Education University of Cape Coast Central Region Cape Coast Ghana Parul University Gujarat Vadadora India

ISBN: (纸本)9798400717468

images are often used as teaching resources in various ways to support teaching. Teachers may use different colors for the same image to teach the same concept. Color is a visual stimulus to the human eye, which may get a child’s attention or not. Attention is also a key element in memory retention, so it is necessary to determine the impact of the color format of an educational image on memory retention. Although there are a number of studies on color’s effects on memory retention, only a few have examined the color scheme of an image. Another gap identified in the review is that children have not been mainly involved in the various studies on how color affects memory retention. Therefore, this review was needed. It is recommended that a scientific study of how the color scheme of a particular type of educational image affects a child’s memory retention is embarked on. This paper serves as an additional source of knowledge and aid in developing digital educational materials. © 2024 Copyright held by the owner/author(s).

关键词： Color image processing

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Missing Person Recognition Algorithms Based on image Captioning and visual Grounding 27th

Missing Person Recognition Algorithms Based on Image Captio...

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27th International conference on Pattern Recognition, ICPR 2024

作者： Jeong, Ayeong Woo, Yeongju Kim, Han-Young Suh, Gayun Heo, Chae-Yeon Cho, Yeong-Jun Jeong, Hieyong Department of Artificial Intelligence Chonnam National University 77 Yongbong-ro Buk-gu Gwangju Gwangju61186 Korea Republic of Department of Artificial Intelligence Convergence Chonnam National University 77 Yongbong-ro Buk-gu Gwangju Gwangju61186 Korea Republic of

ISBN: (纸本)9783031801358

Missing person searches are a critical societal challenge with significant implications for public safety and welfare. This study proposes two novel algorithms for efficient and rapid missing person detection based on video data. The first algorithm, CaptionMP, uses image captioning technology to generate descriptions of individuals’ appearances in video footage, comparing these descriptions to missing person information. The second algorithm, DINOMP, employs visual grounding techniques to detect characteristics of missing persons within video streams directly via text prompts. Both algorithms were fine-tuned using the MALS dataset and demonstrated performance across diverse environmental conditions. Notably, they exhibited robust detection capabilities in low-light environments and with complex clothing patterns. The results showed that our proposed methods have considerable potential in the field of missing person detection, offering a solution to the limitations of traditional pedestrian attribute recognition(PAR) methods. This research is expected to substantially contribute to enhancing the practical applicability of intelligent CCTV systems in missing person searches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Video analysis

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2D visualization of multiple groups of coronavirus gene sequences 3

2D visualization of multiple groups of coronavirus gene sequ...

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3rd International conference on Electrical, Electronics, and Information Engineering, EEIE 2024

作者： Zheng, Huaxian Hou, Junlong Zheng, Jeffrey COMAC Software Co. Ltd. 610299 China Yunnan Communications Vocational and Technical College Yunnan Province 650500 China Yunnan University Yunnan Province 650500 China

ISBN: (纸本)9781510688179

Study Finds Flu Virus Gene Sequences Differ in Each Outbreak. Viruses have been in a state of mutation during the evolutionary process, in which a certain segment of the sequence changes, but there is also a similar distribution of bases. Technological advances have allowed rapid access to coronavirus data, making it difficult to directly analyze large amounts of data. By visualizing the gene sequences into images and analyzing them with mature image processing techniques, we can effectively reveal the association between sequences and base distribution characteristics. In this paper, the visualization method for processing coronavirus gene data is based on the ideas of variational logic, bioinformatics and statistics, Firstly, the gene sequence was segmented, the base sequences were transformed accordingly and the number of bases in each segment was counted to calculate their corresponding probabilities;secondly, the probabilities were transformed using Polar Coordinate System, and then the Gramian matrix are used to map the polar coordinates into matrices, so that the one-dimensional sequences are processed into two-dimensional mapping, and the graphical results are analyzed at last. graphical results can be analyzed. © The Authors.

关键词： Coronavirus

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AltAuthor: A Context-Aware Alt Text Authoring Tool with image Classification and LMM-Powered Accessibility Compliance 25

AltAuthor: A Context-Aware Alt Text Authoring Tool with Imag...

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30th International conference on Intelligent User Interfaces Companion, IUI 2025

作者： Song, Hyungwoo Shin, Minjeong Kim, Yeonjoon Jang, Kyochul Choi, Jaehoon Jung, Hyunggu Suh, Bongwon Department of Intelligence and Information Seoul National University Seoul Korea Republic of Human Centered Computing Lab Seoul National University Seoul Korea Republic of College of Nursing Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798400714092

Web accessibility remains a persistent challenge, particularly in providing appropriate alternative text (alt text) for images that meet the needs of people with visual impairments. Existing tools often generate generic descriptions without taking into account image types and webpage context, leading to alt text that fails to align with established accessibility guidelines. To overcome these limitations, we present AltAuthor, an authoring tool designed to assist developers in managing alt text on existing websites. AltAuthor consists of three key components: (1) image Classifier, which identifies visual content and its type, (2) Alt Text Generator, leveraging a Large Multimodal Model to generate compliant descriptions by incorporating identified image type, webpage context, and Section 508 accessibility guidelines, and (3) Interactive Authoring Interface, allowing developers to customize automated suggestions. Through this integrated approach, AltAuthor provides developers with tools to enhance accessibility management. © 2025 Copyright held by the owner/author(s).

关键词： image classification

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14th International conference on Frontier Computing, FC 2024

14th International Conference on Frontier Computing, FC 2024

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14th International conference on Frontier Computing, FC 2024

ISBN: (纸本)9789819627974

The proceedings contain 104 papers. The special focus in this conference is on Frontier Computing. The topics include: Multimedia Digital AI Painting System Based on Machine Vision Algorithm;intelligent Decision Optimization of Big Data in the Digital Economy Under Deep Reinforcement Learning;development of Virtual Maintenance Training Platform for Electric Motors;design of Automatic Driving and Parking System for New Energy Vehicles Based on Artificial Intelligence;application of Machine Learning Algorithms to Mental Health Data processing for College Students;on the Translation Strategy of "Intangible Cultural Heritage" Based on visual Multimodality;research on the Improvement of Human-Machine Collaborative Machine Translation Model Based on Internet;research on Subway Station Space Design from the Perspective of Regional Culture;application of Intelligent Algorithm in image Recognition Under the Vision of Artificial Intelligence;risk Assessment Model of Electricity Customer Data Based on Dynamic Grid Generation Technology;an Evaluation Model of Equestrian Athletes’ Sense of Speed Based on Inertial Sensor Network;emotion Analysis of Low Resource Domain Based on Transfer Learning and Meta-Learning Methods;digital Technology Integrated with Artificial Intelligence Digital Product Research and Development;research on Artificial Neural Network Prediction of the Strength of Metal-Based Carbon Fiber Reinforced Polymer Layer;Intelligent Recommendation Algorithm for New Media Content Based on AI Technology;design of Daily Life Ability Training System Based on Intelligent Evaluation Algorithm;business Model for Developing Power Load Resources;practice of Artificial Intelligence Technology in Enterprise Human Resource Management;medical Service Management Based on Modern Information Technology;tetris Game System Based on Java.

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A Benchmark and Chain-of-Thought Prompting Strategy for Large Multimodal Models with Multiple image Inputs 27th

A Benchmark and Chain-of-Thought Prompting Strategy for Larg...

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27th International conference on Pattern Recognition, ICPR 2024

作者： Zhang, Daoan Yang, Junming Lyu, Hanjia Jin, Zijian Yao, Yuan Chen, Mingkai Luo, Jiebo University of Rochester Rochester United States Nanjing University of Posts and Telecommunications Nanjing China New York University New York United States Stony Brook University Stony Brook United States

ISBN: (纸本)9783031784552

When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image inputs. However, Large Multimodal Models (LMMs) encounter two issues in such scenarios: (1) a lack of fine-grained perception, and (2) a tendency to blend information across multiple images. To better investigate the capability of LMMs to perceive fine-grained visual details when dealing with multiple input images, we built a benchmark for evaluating LMM with multiple image inputs - MIMU(Muti-image Inputs Multimodal Understanding Benchmark). The benchmark focuses on two scenarios: first, image-to-image matching (to evaluate whether LMMs can effectively reason and pair relevant images), and second, multi-image-to-text matching (to assess whether LMMs can accurately capture and summarize detailed image information). We conduct evaluations on a range of both open-source and closed-source large models, including GPT-4V, Gemini, OpenFlamingo, and MMICL. Although GPT-4V achieves the best results in all metrics, it still has a significant gap from Human Evaluation. To enhance model performance, we further develop a Contrastive Chain-of-Thought (CoCoT) prompting approach based on multi-input multimodal models. This method requires LMMs to compare the similarities and differences among multiple image inputs, and then guide the models to answer detailed questions about multi-image inputs based on the identified similarities and differences. Our experimental results showcase CoCoT’s proficiency in enhancing the multi-image comprehension capabilities of large multimodal models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Artificial intelligence

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14th International conference on Frontier Computing, FC 2024

14th International Conference on Frontier Computing, FC 2024

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14th International conference on Frontier Computing, FC 2024

ISBN: (纸本)9789819623945

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