217 Result(s)
within
Computer Science
Information Storage and Retrieval
Pattern Recognition
Fu** Lin
Chapter
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Chapter and Conference Paper
TalkSee: Interactive Video Retrieval Engine Using Large Language Model
The current interactive retrieval system mostly relies on collecting user’s positive and negative feedback and updating the retrieval content based on this feedback. However, this method is not always sufficie...
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Chapter and Conference Paper
Hierarchical Bi-directional Temporal Context Mining for Improved Video Compression
Bidirectional video compression leverages information from both past and future frames to assist in compressing video frames. In this paper, we propose a novel multi-scale bidirectional context-aware adaptive ...
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Chapter and Conference Paper
Face Forgery Detection via Texture and Saliency Enhancement
In recent years, AI-driven advancements have resulted in increasingly sophisticated face forgery techniques, posing a challenge in distinguishing genuine images from manipulated ones. This presents significant...
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Chapter and Conference Paper
MAMixer: Multivariate Time Series Forecasting via Multi-axis Mixing
Sensor data, such as traffic flow monitoring data, constitutes a type of multimedia data. Forecasting sensor data holds significant potential for decision-making. And we can explore its patterns using time ser...
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Chapter and Conference Paper
Removing Stray-Light for Wild-Field Fundus Image Fusion Based on Large Generative Models
In low-cost wide-field fundus cameras, the built-in lighting sources are prone to generate stray-light nearby, leading to low-quality image regions. To visualize retinal structures clearer, when fusing two ima...
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Chapter and Conference Paper
DHP: A Joint Video Download and Dynamic Bitrate Adaptation Algorithm for Short Video Streaming
With the development of multimedia technology and the upgrading of mobile terminal equipment, short video platforms and applications are becoming more and more popular. Compared with traditional long video, sh...
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Chapter and Conference Paper
Interpretable Driver Fatigue Estimation Based on Hierarchical Symptom Representations
Traffic accidents caused by driver fatigue lead to millions of death and financial loss every year. Current end-to-end methods for driver fatigue detection are not capable of distinguishing the detailed fatigu...
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Chapter and Conference Paper
Multi-view Adaptive Bone Activation from Chest X-Ray with Conditional Adversarial Nets
Activating bone from a chest X-ray (CXR) is significant for disease diagnosis and health equity for under-developed areas, while the complex overlap of anatomical structures in CXR constantly challenges bone a...
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Chapter and Conference Paper
Transferable Adversarial Attack on 3D Object Tracking in Point Cloud
3D point cloud tracking has recently witnessed considerable progress with deep learning. Such progress, however, mainly focuses on improving tracking accuracy. The risk, especially considering that deep neural...
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Chapter and Conference Paper
Video-Based Precipitation Intensity Recognition Using Dual-Dimension and Dual-Scale Spatiotemporal Convolutional Neural Network
This paper proposes the dual-dimension and dual-scale spatiotemporal convolutional neural network, namely DDS-CNN, which consists of two modules, the global spatiotemporal module (GSM) and the local spatiotemp...
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Chapter and Conference Paper
Spatial Attention and Syntax Rule Enhanced Tree Decoder for Offline Handwritten Mathematical Expression Recognition
Offline Handwritten Mathematical Expression Recognition (HMER) has been dramatically advanced recently by employing tree decoders as part of the encoder-decoder method. Despite the tree decoder-based methods r...
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Chapter and Conference Paper
An Efficient Prototype-Based Model for Handwritten Text Recognition with Multi-loss Fusion
Prototype learning has achieved good performance in many fields, showing higher flexibility and generalization. In this paper, we propose an efficient text line recognition method based on prototype learning w...
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Chapter and Conference Paper
EAU-Net: A New Edge-Attention Based U-Net for Nationality Identification
Identifying crime or individuals is one of the key tasks toward smart and safe city development when different nationals are involved. In this regard, identifying Nationality/Ethnicity through handwriting has ...
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Chapter and Conference Paper
Dewar** Document Image by Displacement Flow Estimation with Fully Convolutional Network
As camera-based documents are increasingly used, the rectification of distorted document images becomes a need to improve the recognition performance. In this paper, we propose a novel framework for both recti...
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Chapter and Conference Paper
Page Segmentation Using Convolutional Neural Network and Graphical Model
Page segmentation of document images remains a challenge due to complex layout and heterogeneous image contents. Existing deep learning based methods usually follow the general semantic segmentation or object ...
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Chapter and Conference Paper
Accelerating Topic Detection on Web for a Large-Scale Data Set via Stochastic Poisson Deconvolution
Organizing webpages into hot topics is one of the key steps to understand the trends from multi-modal web data. To handle this pressing problem, Poisson Deconvolution (PD), a state-of-the-art method, recently ...
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Chapter and Conference Paper
An Effective Dual-Fisheye Lens Stitching Method Based on Feature Points
Fisheye lens is a super-wide-angle lens which is very light. Usually two cameras can shoot 360-degree panoramic images. However, the limited overlap** field of views make it hard to stitch in the boundaries....
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Chapter and Conference Paper
A Novel Ensemble Approach for Click-Through Rate Prediction Based on Factorization Machines and Gradient Boosting Decision Trees
Click-Through Rate (CTR) prediction is a significant technique in the field of computational advertising, its accuracy directly affects companies profits and user experience. Achieving great ability of general...
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Chapter and Conference Paper
Using Sentiment Representation Learning to Enhance Gender Classification for User Profiling
User profiling means exploiting the technology of machine learning to predict attributes of users, such as demographic attributes, hobby attributes, preference attributes, etc. It’s a powerful data support of ...
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Chapter and Conference Paper
PKRS: A Product Knowledge Retrieve System
In this demo paper, we present the Product Knowledge Retrieve System (PKRS), which can retrieve the large-scale product knowledge efficiently. The PKRS has three features. Firstly, PKRS can retrieve not only t...
