74 Result(s)
within
Computer Science
Computer Communication Networks
Qing-**ang Wang
Chapter
Conference Paper
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Chapter and Conference Paper
Mining Regional High Utility Co-location Pattern
A co-location pattern is a set of spatial features whose instances are frequently located together in geo-space. In real world, different instances have different distributions and different values. However, e...
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Chapter and Conference Paper
Deep Forest Model Combined with Neural Networks for Finger Joint Continuous Angle Decoding
Many people lose their hand function due to stroke, traffic accidents, and amputation. This paper proposed a new method that can decode hand joint angles from the upper limb’s surface electromyography (sEMG). ...
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Chapter and Conference Paper
CrowdFusion: Refined Cross-Modal Fusion Network for RGB-T Crowd Counting
Crowd counting is a crucial task in computer vision, offering numerous applications in smart security, remote sensing, agriculture and forestry. While pure image-based models have made significant advancements...
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Chapter and Conference Paper
Niagara: Scheduling DNN Inference Services on Heterogeneous Edge Processors
Intelligent applications heavily rely on deep neural network (DNN) inference services executed on edge devices to fulfill functional prerequisites while safeguarding user data privacy. However, the execution o...
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Chapter and Conference Paper
A Secure Sharing Framework Based on Cloud-Chain Fusion for SWIM
The air traffic management (ATM) data sharing has attracted extensive attention as the key content of the collaborative operation in the next generation of aviation sector, and the corresponding secure issues ...
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Chapter and Conference Paper
The Storage and Sharing of Big Data in Air Traffic Management System
With the continuous development of aviation business and informatization, the storage and sharing mechanism based on big data will play a more important role in the next generation Air Traffic Management (ATM)...
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Chapter and Conference Paper
FedGR: Federated Learning with Gravitation Regulation for Double Imbalance Distribution
Federated Learning (FL) is a well-known framework for distributed machine learning that enables mobile phones and IoT devices to build a shared machine learning model via only transmitting model parameters to ...
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Chapter and Conference Paper
Pairing-Free Certificateless Key-Insulated Encryption with Keyword Search
Public key encryption with keyword search (PEKS) allows a user to make searches on ciphertexts without disclosing the information of encrypted messages and keywords. The certificateless public key encryption w...
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Chapter and Conference Paper
Few-Shot Generative Learning by Modeling Stereoscopic Priors
Few-shot image generation, which aims to generate images from only a few images for a new category, has attracted some research interest in recent years. However, existing few-shot generation methods only focu...
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Chapter and Conference Paper
A Road Congestion Detection Model Based on Sequence Change of Vehicle Feature Matrix
In order to solve the problem of urban road congestion, this paper proposes a road congestion detection model based on the sequence change of vehicle feature matrix. The model uses the YOLO_V3 deep learning mo...
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Chapter and Conference Paper
Prognostic Staging System for Esophageal Cancer Using Lasso, Cox and CS-SVM
Esophageal cancer is a heterogeneous malignant tumor with high mortality. Design constructing an effective prognostic staging system would help to improve the prognosis of patients. In this paper, blood indexe...
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Chapter and Conference Paper
An Adaptive Weight Joint Loss Optimization for Dog Face Recognition
In recent years, the field of human face recognition has developed rapidly, and a large number of deep learning methods have proven their efficiency in human face recognition. However, these methods do not wor...
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Chapter and Conference Paper
Lightweight Image Compression Based on Deep Learning
Deep learning based image compression (DLIC) algorithms have achieved higher compression gain than conventional algorithms. However, the large parameters and float-point operations (FLOPs) of DLIC severely lim...
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Chapter and Conference Paper
Blockchain-as-a-Service Powered Knowledge Graph Construction
The growing interest in the knowledge graph has attracted a great attention from both academia and the industry. Blockchain-based knowledge construction is deemed to be an alternative by adopting smart contrac...
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Chapter and Conference Paper
Recommendation Model Based on Social Homogeneity Factor and Social Influence Factor
In recent years, more and more recommendation algorithms incorporate social information. H...
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Chapter and Conference Paper
Quantitative Data Cleaning and Analysis for Large Databases of Passenger Car Fuel Consumptions
This paper presents the work a development of data cleaning and analysis for on-board diagnostic system (OBD II) data. The OBD device can collect speed and mass air flow via ECU, from which the instantaneous f...
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Chapter and Conference Paper
Learning Modality-Invariant Features by Cross-Modality Adversarial Network for Visual Question Answering
Visual Question Answering (VQA) is a typical multimodal task with significant development prospect on web application. In order to answer the question based on the corresponding image, a VQA model needs to utiliz...
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Chapter and Conference Paper
VTLayout: Fusion of Visual and Text Features for Document Layout Analysis
Documents often contain complex physical structures, which make the Document Layout Analysis (DLA) task challenging. As a pre-processing step for content extraction, DLA has the potential to capture rich infor...
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Chapter and Conference Paper
Chinese Named Entity Recognition Based on Dynamically Adjusting Feature Weights
Named entity recognition is a basic task in NLP, and it is an important basic tool for many NLP tasks such as information extraction, parsing, question answering system and machine translation. The extraction ...
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Chapter and Conference Paper
Research on Accurate Location of Line Loss Anomaly in Substation Area Based on Data Driven
We proposed a data mining-based method for precise positioning method of users associated with abnormal line loss. First, we based on the gap statistical algorithm (GSA) to determine the optimal number of clus...
