927 Result(s)
within
Computer Science
Artificial Intelligence
Information Storage and Retrieval
Fu** Lin
Chapter
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Chapter and Conference Paper
An Improved Algorithm with Azimuth Clustering for Detecting Turning Regions on GPS Trajectories
According to the latest report released by the Ministry of Agriculture (MOA) of Taiwan, the number of agriculture machinery in Taiwan exceeds 200,000. To keep track of these machinery, there are some research ...
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Chapter and Conference Paper
Privacy-Preserving Medical Dialogue Generation Based on Federated Learning
Large-scale pre-trained dialogue models have shown outstanding performance across various dialogue-related natural language processing tasks. However, in privacy-sensitive domains like healthcare, concerns rel...
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Chapter and Conference Paper
A Medical Diagnostic Assistant Based on LLM
With the advent of ChatGPT, large language models (LLMs) have received extensive attention because of their excellent instruction comprehension and generation capabilities. However, LLMs are not specifically d...
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Chapter and Conference Paper
An Egg Sorting System Combining Egg Recognition Model and Smart Egg Tray
Modern agriculture is at the forefront of technological transformation. Smart agricultural technology and mechanical automation are bringing unprecedented opportunities and challenges to the field. This study ...
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Chapter and Conference Paper
Blockchain-Based Diagnostic Certificate System with Privacy Protection
Blockchain represents a novel form of information technology application. It offers promising potential for future transactions and practical applications, particularly through the implementation of smart cont...
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Chapter and Conference Paper
Facial Nerve Disorder Rehabilitation via Generative Adversarial Network
With the rapid growth in the number of patients with facial nerve disorders, the cost of therapy is continually increasing, thus placing both physical and financial burdens on patients. Patients with facial ne...
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Chapter and Conference Paper
Integration of Convolutional Neural Networks and Autoencoding for Generating Reconfigurable Intelligent Surfaces
This paper presents a method utilizing convolutional neural networks (CNN) and autoencoding for generating a reconfigurable intelligent surface (RIS) based on information like beam angles and radiation pattern...
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Chapter and Conference Paper
Optimal Truncated MobileNet-Based Image Binarization for Pose-Based Visual Servoing of Autonomous Mobile Robot
Pose-based visual servoing (PBVS) can complement the frequent drift issue of light detection and ranging (LiDAR) coordinate of LiDAR-based simultaneous localization and map** (SLAM), navigation, and servoing...
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Chapter and Conference Paper
Design and Implementation of Optical Lens Defect Detection and Classification System
The glass lens production process requires cutting, grinding and polishing, it is easy to cause lens defects, and the production quality needs to be maintained through inspection. In the past, people relied on...
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Chapter and Conference Paper
A Mixture-of-Experts (MoE) Framework for Pose-Invariant Face Recognition via Local Landmark-Centered Feature Extraction
Most real-world applications in video surveillance and biometric authentication rely on robust face recognition systems capable of dealing with multiple variations of pose, illumination, and expression within ...
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Chapter and Conference Paper
Air Pollution Source Tracing Framework: Leveraging Microsensors and Wind Analysis for Pollution Source Identification
In the context of rapid urbanization, air pollution has become a significant concern, particularly in densely developed urban areas
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Chapter and Conference Paper
Biomedical Relation Extraction via Syntax-Enhanced Contrastive Networks
Extracting biomedical relations from biomedical literature automatically is essential for discovering new biomedical knowledge. However, in the biomedical domain, some texts with different types have semantic ...
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Chapter and Conference Paper
Context Enhanced Recurrent Neural Network for Session-Aware Recommendation
Recommender systems, which suggest items that users might find most interesting based on their previous web-clicks or purchased items, have a wide range of applications. While recent methods employing recurren...
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Chapter and Conference Paper
Semantic and Emotional Feature Fusion Model for Early Depressive Prediction
In recent years, depression has caused severe social and psychological problems. The purpose of the paper is to automatically identify users with depressive tendencies to facilitate early intervention and prev...
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Chapter and Conference Paper
Entity Fusion Contrastive Inference Network for Biomedical Document Relation Extraction
In recent years, the field of biomedical information has experienced remarkable growth. Consequently, the extraction of semantic relationships between biological entities from unstructured biomedical documents...
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Chapter and Conference Paper
Double Graph Convolution Network with Knowledge Distillation for International Media Portrait Analysis of COVID-19
Global media with international influence play a crucial role in sha** international public opinion related to China. These media report on objective events and shape people’s perceptions and viewpoints. So,...
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Chapter and Conference Paper
Handling Concept Drift in Non-stationary Bandit Through Predicting Future Rewards
We present a study on the non-stationary stochastic multi-armed bandit (MAB) problem, which is relevant for addressing real-world challenges related to sequential decision-making. Our work involves a thorough ...
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Chapter and Conference Paper
Exploiting Style Transfer and Semantic Segmentation to Facilitate Infrared and Visible Image Fusion
Image fusion integrates different imaging sources to generate one with improved scene representation or visual perception, supporting advanced vision tasks such as object detection and semantic analysis. Fusin...
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Chapter and Conference Paper
Multi-head Attention and Graph Convolutional Networks with Regularized Dropout for Biomedical Relation Extraction
Automatic extraction of biomedical relation from text becomes critical because manual relation extraction requires significant time and resources. The extracted medical relations can be used in clinical diagno...
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Chapter and Conference Paper
From SMOTE to Mixup for Deep Imbalanced Classification
Given imbalanced data, it is hard to train a good classifier using deep learning because of the poor generalization of minority classes. Traditionally, the well-known synthetic minority oversampling technique ...
