16 Result(s)
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Chapter and Conference Paper
Pacesetter Learning for Large Scale Cooperative Multi-Agent Reinforcement Learning
In complex multi-agent reinforcement learning environments, such as Starcraft II, most existing algorithms struggle to scale up to large-scale collaboration tasks. This is partly because learning to precisely ...
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Chapter and Conference Paper
An Exploration of Barrier-Free Driving Education Assistance System Based on HCI Technology Under the Inclusive Design Concept
The massive integration of mobile Internet technology in vehicles led to the launch on the market of many advanced driving assistance systems, with constantly increasing functions and novel modes of interactio...
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Chapter and Conference Paper
Robust Multi-view Registration of Point Sets with Laplacian Mixture Model
Point set registration is an essential step in many computer vision applications, such as 3D reconstruction and SLAM. Although there exist many registration algorithms for different purposes, however, this top...
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Chapter and Conference Paper
PromptMNER: Prompt-Based Entity-Related Visual Clue Extraction and Integration for Multimodal Named Entity Recognition
Multimodal named entity recognition (MNER) is an emerging task that incorporates visual and textual inputs to detect named entities and predicts their corresponding entity types. However, existing MNER methods...
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Chapter and Conference Paper
Rotation-DPeak: Improving Density Peaks Selection for Imbalanced Data
Density Peak (DPeak) is an effective clustering algorithm. It maps arbitrary dimensional data onto a 2-dimensional space, which yields cluster centers and outliers automatically distribute on upper right and u...
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Chapter and Conference Paper
Cross-modal Deep Learning Applications: Audio-Visual Retrieval
Recently, deep neural networks have exhibited as a powerful architecture to well capture the nonlinear distribution of high-dimensional multimedia data such as image, video, text and audio, so naturally does f...
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Chapter and Conference Paper
Real-Time Recognition of Motor Vehicle Whistle with Convolutional Neural Network
This paper proposes a method based on convolutional neural network (CNN) to recognition of motor vehicle whistle, which is used to monitor illegal whistle. The convolutional neural network architecture takes t...
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Chapter and Conference Paper
Effect Analysis and Method Suggestions of Online Learning Under the Public Epidemic Crisis
In the context of a major national public epidemic caused by COVID-19, the education system has also been greatly affected, changing from traditional offline education to online education. In the case of chang...
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Chapter and Conference Paper
Analysis on the Application of AI Technology in Online Education Under the Public Epidemic Crisis
In order to prevent the spread of COVID-19, online education has become a learning way for primary and secondary schools and universities. However, the rapid development of online education faces many challeng...
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Chapter and Conference Paper
Active Learning for Auditory Hierarchy
Much audio content today is rendered as a static stereo mix: fundamentally a fixed single entity. Object-based audio envisages the delivery of sound content using a collection of individual sound ‘objects’ con...
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Chapter and Conference Paper
Urban Interaction Design Supports Modular Design Practice for Urban Public Space
Multiple-dimensional structured urban space directs to an inter-disciplinary considers on public space utilization. The people-users are consciously and unconsciously in the communicative activities with the c...
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Chapter and Conference Paper
Computing Image Intersection and Union Regions for Drosophila Neurons Based on Multi-core CPUs
With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosop...
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Chapter and Conference Paper
A Deep Learning Method for Prediction of Benign Epilepsy with Centrotemporal Spikes
Benign epilepsy with centrotemporal spikes (BECT) is the most common epilepsy in the children. The research of BECT mainly focuses on the comparative analysis of the BECT patients and the healthy controls. Dif...
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Chapter and Conference Paper
Learning 3D Keypoint Descriptors for Non-rigid Shape Matching
In this paper, we present a novel deep learning framework that derives discriminative local descriptors for 3D surface shapes. In contrast to previous convolutional neural networks (CNNs) that rely on renderin...
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Chapter and Conference Paper
User-Oriented Social Analysis across Social Media Sites
The vast amount of user-generated data in various and disparate social media sites contains rich and diverse information about what is happening around the world. Digging into such user-generated data distribu...
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Chapter and Conference Paper
The Canny Edge Detection and Its Improvement
To solve the problem of the traditional Canny edge detection operator has the weaknesses in excessive smoothing image and adaptability, and improved the parameter Sigma and the method to obtain high threshold....
