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检索条件"任意字段=5th International Conference on Machine Learning and Human-Computer Interaction, MLHMI 2024"

共 558 条记录，以下是311-320 订阅

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D-CBAMFi: A Lightweight Multi-Scale Fusion Network Based on Depthwise Separable Convolution and Dilated Convolution

D-CBAMFi: A Lightweight Multi-Scale Fusion Network Based on ...

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Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Zhen Li Zhibiao Zhao Yulang He Yan Shi Qi Zhou Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

Gesture recognition is crucial for the development of new human-computer interaction paradigms that will change the interaction between humans and their surroundings. Most deep learning-based techniques use neural networks with a single backbone architecture, which can only capture a single feature and cannot meet the requirements of real-world applications for recognition tasks in resource-limited and complex scenarios. therefore, we propose a lightweight multi-scale fusion network, D-CBAMFi, whose core component is a D-CBAM network consisting of parallel depth-wise separable convolution and dilated convolution and CBAM. the proposed system achieves an average accuracy of 84.30% on the Widar dataset, validating the effectiveness of the model.

关键词： human computer interaction Convolution Computational modeling Neural networks Gesture recognition Feature extraction Spatiotemporal phenomena Sensors Data mining Wireless fidelity

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Enhancing Multi-Agent Reinforcement learning via Entity Aware-interaction Network

Enhancing Multi-Agent Reinforcement Learning via Entity Awar...

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Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Xinyu Shen School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

this paper addresses a significant challenge in multi-agent reinforcement learning (MARL): the paradoxical underperformance of theoretically superior algorithms like QTRAN compared to simpler ones such as QMIX and VDN in practical applications. We identify the root cause as inefficient network representations in QTRAN implementations. To resolve this, we propose a novel, high-efficiency network structure incorporating relational graph network and attention graph network modules. this structure significantly enhances QTRAN's sample efficiency and overall performance. By conceptualizing multi-agent systems as graph structures, our approach enables more effective representation of agent interactions and relationships. Experimental results demonstrate that our enhanced QTRAN outperforms state-of-the-art algorithms like QMIX and VDN in benchmark environments. this work contributes to bridging the gap between theoretical advancements and practical performance in MARL, particularly in fully cooperative tasks.

关键词： human computer interaction Attention mechanisms Scalability Heuristic algorithms Estimation Reinforcement learning Information processing Benchmark testing Network architecture Multi-agent systems

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Magnetic Resonance Imaging-based Prostate Cancer Detection and Classification using machine learning and Deep learning Techniques: A Survey

Magnetic Resonance Imaging-based Prostate Cancer Detection a...

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Mobile Computing and Sustainable Informatics (ICMCSI), international conference on

作者： Nasser M. Al-Zidi D. Vasumathi Department of Computer Science and Engineering College of Engineering Jawaharlal Nehru Technological University Hyderabad Hyderabad India

Prostate cancer (PCa) ranks second among the most common cancers in men globally, with a staggering 1.4 million new cases estimated in 2020. Due to the increasing number of cases of this type of cancer, the detection and classification of PCa is one of the challenges for early treatment and increasing human survival chances. In recent years, several studies focused on identifying PCa. In the detection and classification of prostate cancer (PCa), magnetic resonance imaging (MRI) assumes a crucial role. machine learning (ML) and Deep learning (DL) can accurately and rapidly analyze MRI images and could provide better standardization and consistency in detecting PCa. this review summarizes studies that used ML and DL techniques on prostate MRI and focused on PCa detection and classification. the studies reviewed varied in performing prostate organ segmentation and approximation, prostate lesion characterization, and prostate lesion detection and segmentation. Derived from the good outcomes observed in the analysis of these studies, despite the difficulties and the presence of unsolved problems, it was concluded that the techniques based on ML and DL are adequate and promising for the detection and classification of PCa.

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Efficient Business Meeting Summarization: Leveraging Natural Language Processing for Enhanced Productivity 5th

Efficient Business Meeting Summarization: Leveraging Natural...

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5th international conference on Recent Trends in machine learning, IoT, Smart Cities, and Applications, ICMISC 2024

作者： Shanthamalar, J. Jeslin Nithya, S. Kumar, Alle Nithin Chandra, Beraboina Jaya Nancy Noella, R.S. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9789819788644

In the contemporary corporate landscape, efficient utilization of time is paramount for organizational success. Business meetings, a fundamental component of decision-making processes, often result in copious amounts of information exchange. this project aims to streamline and enhance the post-meeting experience through the development of an Automated Business Meeting Summarization system. Additionally, the system employs sentiment analysis to gauge the overall tone and mood of the meeting, providing valuable insights into team dynamics and engagement levels. the project aims to empower organizations with an efficient tool that not only accelerates the decision-making process but also fosters better collaboration and understanding among team members. In contrast, zero-shot Whisper models demonstrate a robustness frontier that includes the 95% confidence interval for human performance. the BART-large-CNN-SAMSum model demonstrates promising performance on the SAMSum summarization dataset, achieving a ROGUE-1 score of 42.621. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sentiment analysis

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Efficient Mastery of Gomoku Game through Deep Monte Carlo Method

Efficient Mastery of Gomoku Game Through Deep Monte Carlo Me...

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Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Gang Wang Zhanggen Jin Changming Xu Junwei Wang School of Computer Science and Engineering Northeastern University Liaoning China School of Computer and Communication Engineering Northeastern University at Qinghuangdao Hebei China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

Deep reinforcement learning has made significant progress in the field of computer games. Traditional methods typically involve extensive tree expansion and simulation during the self-play phase to generate large amounts of match data for training models, which requires substantial computational resources. To reduce reliance on high computational resources, we abandoned the traditional self-play method and adopted a deep Monte Carlo method to generate match data in batches on GPUs, without relying on tree expansion. When applying this method to the game of Gomoku, the results showed that under limited computational resources, this method achieved a faster increase in Elo rating compared to traditional methods and exhibited faster convergence during training. Moreover, agents using this method ranked first among 503 agents on Peking University's BotZone platform.

关键词： Training human computer interaction Video games Monte Carlo methods Training data Games Deep reinforcement learning Stability analysis Hardware thermal stability

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Multimodal Integration, Fine Tuning of Large Language Model for Autism Support

Multimodal Integration, Fine Tuning of Large Language Model ...

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Mobile Computing and Sustainable Informatics (ICMCSI), international conference on

作者： Krishna Pai Vidhita Jagwani Shivalik Pandita Dhananjay Kalbande Department of Computer Engineering Sardar Patel Institute of Technology Mumbai India Department of Computer Science and Engineering Sardar Patel Institute of Technology Mumbai India

this research project centres on creating an inclusive environment for the specially-abled. Created an app that integrates real-time object detection and speech-to-text capabilities which provides a multi-modal user experience with the pre-trained Model. Incorporated parameter-efficient fine-tuning using Low-Rank Adaptation (LoRA) to emulate the behaviour of an autism *** second module of the research employs YOLOv5 and machine learning to analyze therapy videos to get interaction timestamps and statistical insights. It automates the identification of interactions and serves as a valuable aid to guardians and *** paper details the methodology for real-time object detection using YOLO, SSD Mobilenet and enhances understanding in the context of adaptation of Language Models for a particular use case. Furthermore, dives deeper into the intricacies of interaction monitoring using bounding boxes in *** pushing the boundaries of Large Language Model capabilities, this research not only refines language models but also lays the foundation for their application in dynamic contexts of the real world, exemplifying their revolutionary potential.

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A Visual Monitoring Method for Monochromators Based on Video Super-Resolution and Kalman Filter

A Visual Monitoring Method for Monochromators Based on Video...

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Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Zhijuan Li Shiwei Ma School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

To achieve real-time and precise monitoring of the main moving component of the monochromator. We have developed a visual monitoring system for monochromator based on machine vision technology for SSRF. To enhance the accuracy and stability of visual detection, this paper proposes a visual monitoring method that integrates video super-resolution (VSR) and kalman filter (KF) with YOLOv5 object detection. First, VSR is applied to enhance the quality of images captured by the camera. then, scale numbers on a ruler are detected, and KF is employed for stable tracking of the scale numbers' detection boxes. Finally, the position of the monitored subjects is calculated based on tracking results of the scale numbers on the ruler. Experimental results demonstrate that by implementing VSR, the detection rate of scale numbers improved by an average of 12%, and in combination with the tracking algorithm based on KF, the proposed method achieves enhanced stability in the positioning of the moving component in the monochromator.

关键词： YOLO human computer interaction Visualization machine vision Superresolution Streaming media Filtering algorithms Real-time systems Kalman filters Monitoring

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User Experience and Fuzzy Evaluation for Intelligent Cockpit

User Experience and Fuzzy Evaluation for Intelligent Cockpit

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Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Peiyao Wang Xuhua Shi Hongzan Xu Gaoran Zhang Xiaojun Tang The College of Information Science and Engineering NingBo University NingBo China ZEEKR Auto (Ningbo Hangzhou Bay New Area) Co. Ltd. NingBo China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

An intelligent cockpit user experience evaluation model is introduced, utilizing a three-level indicator system based on the fuzzy analytic hierarchy process. the first-level indicators encompass hardware, software functionality, perceptual experience, and emotional experience. Hardware and software, being fundamental cockpit's features, are pivotal to the overall user experience. Based on this, multimodal perceptual experience enhances user awareness and emotional experience reflects the user's psychological acceptance of the entire interaction process and outcomes, representing the culmination of the user's experience within the intelligent cockpits. Experimental results show that, when faced with numerous evaluation indicators, the proposed method outperforms traditional approaches, offering greater efficiency and reducing human subjectivity and uncertainty, thereby facilitating user experience evaluation. the studies presented can guide the user experience design for automobile intelligent cockpits.

关键词： Fuzzy sets Accuracy Statistical analysis Evaluation models User centered design machine learning User experience Software Hardware Automobiles

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Posture Planning Study of Manual Assembly Operations in Narrow Spaces

Posture Planning Study of Manual Assembly Operations in Narr...

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Intelligent Computing and human-computer interaction (ICHCI), international conference on

作者： Yizhen Zheng Yuefeng Li Hongyan Zhao Fanwei Meng Yuan Liu College of Electromechanical Engineering Harbin Institute of Technology Harbin Heilongjiang China Beijing Institute of Spacecraft Environment Engineering Beijing China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

Aiming at the constraints of manual assembly operation in narrow space, a multi-objective attitude optimization model is constructed by combining the balance, reachability, collision detection and other factors of human attitude. Specifically, the coupling relationship between the manual assembly operation posture in narrow space and the balance, target visibility, joint angle and operation target reachability is first analyzed. then, the functional relationship between the human assembly operation posture and the above influencing factors is established, and the multi-objective optimization model of the assembly operation posture in narrow space is constructed. Finally, NSGA-III(Non-dominated Sorting Genetic Algorithm III) multi-objective genetic algorithm is used to solve the model and realize the attitude planning of assembly operation in narrow space.

关键词： human computer interaction Couplings Optimization models human-machine systems Pareto optimization Planning Assembly Optimization Genetic algorithms Sorting

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Real-Time Facial Expression Recognition Using Convolutional Neural Networks for Adaptive User Interfaces

Real-Time Facial Expression Recognition Using Convolutional ...

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Emerging Technology (INCET), international conference for

作者： Jerry Jatan Sundi Hitesh Kumar Bharti Rajnish Bedi Department of Computer Science and Engineering Chandigarh University Mohali India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

Facial expression recognition plays a crucial role in enabling natural and intuitive human-computer interaction. However, existing approaches often struggle with robustness and accuracy, particularly in unconstrained environments with varying illumination, occlusions, and pose variations. this research proposes a novel real-time facial expression recognition system based on convolutional neural networks (CNNs) to address these challenges. the proposed system leverages state-of-the-art deep learning architectures and techniques to accurately recognize a wide range of facial expressions in real-time. through extensive data preprocessing, augmentation, and a carefully designed CNN architecture, the system aims to achieve high accuracy and generalization capabilities across diverse scenarios. the recognized facial expressions are then utilized to enable adaptive user interfaces that can dynamically adapt to the user's emotional state, enhancing the overall user experience. Comprehensive experiments and user studies are conducted to evaluate the system's performance, robustness, and effectiveness in improving human-computer interaction. the proposed approach has the potential to significantly impact various domains, including gaming, healthcare, education, and beyond, by enabling emotion-aware computing and personalized interfaces.

关键词： human computer interaction Accuracy Face recognition System performance machine vision Medical services Real-time systems

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