Tianyu Gu
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Author Swipe
View article: Fusion calib: azimuth angle and multi frame tracking for online extrinsic radar-camera calibration
Fusion calib: azimuth angle and multi frame tracking for online extrinsic radar-camera calibration Open
Traditional radar-camera calibration requires manual intervention and excessive computational resources, resulting in high labor costs for maintenance in roadside perception scenarios. Thus, we propose a continuous online calibration metho…
View article: Mapping Global Research Landscapes of Acupuncture for Diabetes Mellitus: A 20-Year Bibliometric Study (2004–2024)
Mapping Global Research Landscapes of Acupuncture for Diabetes Mellitus: A 20-Year Bibliometric Study (2004–2024) Open
Background: As diabetes mellitus continues to escalate into a global health crisis, particularly in China, the limitations of conventional pharmacotherapy underscore the need for complementary interventions. This study systematically revie…
View article: Low toxicity mechanistic insights into Z-scheme WO3/BiFeO3/DSB photocatalysts for efficient ampicillin degradation
Low toxicity mechanistic insights into Z-scheme WO3/BiFeO3/DSB photocatalysts for efficient ampicillin degradation Open
Ampicillin (AMP) poses a significant environmental hazard to aquatic ecosystems, and previous research has been inadequate in addressing the ecological toxicity of its byproducts. A novel photocatalyst, WO3-BiFeO3/digestate biochar (DSB), …
View article: MC-GAT: Multi-channel Graph Attention Networks for capturing diverse information in complex graph
MC-GAT: Multi-channel Graph Attention Networks for capturing diverse information in complex graph Open
Much attention has been paid to Graph Attention Networks (GAT), which excel at various analytical tasks involving graph and network data. However, complex real-world networks have both edge topology and node features. GAT only relies on th…
View article: Differences in Relational Schemas between Optimism and Pessimism
Differences in Relational Schemas between Optimism and Pessimism Open
This paper creates a new approach to studying relational schemas. The idea of our experiment started with an essay called Relational schemas, self-esteem, and the processing of social stimuli, which is written by Erika J. Koch. She mainly …
View article: Multi-Task Joint Learning Model for Chinese Word Segmentation and Syndrome Differentiation in Traditional Chinese Medicine
Multi-Task Joint Learning Model for Chinese Word Segmentation and Syndrome Differentiation in Traditional Chinese Medicine Open
Evidence-based treatment is the basis of traditional Chinese medicine (TCM), and the accurate differentiation of syndromes is important for treatment in this context. The automatic differentiation of syndromes of unstructured medical recor…
View article: Liraglutide Nano-Preparation on Perioperative Neurocognitive Dysfunction in Aged Mice
Liraglutide Nano-Preparation on Perioperative Neurocognitive Dysfunction in Aged Mice Open
At present, there is not enough research about the application of liraglutide nano preparations in perioperative neurocognitive dysfunction. Therefore, the purpose of this study is the mechanism of the effect of liraglutide nano preparatio…
View article: Comparisons of the Different Views of Face Negotiation Theory
Comparisons of the Different Views of Face Negotiation Theory Open
View article: Analyzing Unstructured Data for Marketing Insights
Analyzing Unstructured Data for Marketing Insights Open
In this dissertation, I am focused on analyzing the effects of information embedded in unstructured data on consumer decisions and firm strategies. Mining unstructured data (such as natural language and visual imagery) for insights and imp…
View article: BadNets: Evaluating Backdooring Attacks on Deep Neural Networks
BadNets: Evaluating Backdooring Attacks on Deep Neural Networks Open
Deep learning-based techniques have achieved state-of-the-art performance on a wide variety of recognition and classification tasks. However, these networks are typically computationally expensive to train, requiring weeks of computation o…
View article: Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator
Analyzing and Mitigating the Impact of Permanent Faults on a Systolic Array Based Neural Network Accelerator Open
Due to their growing popularity and computational cost, deep neural networks (DNNs) are being targeted for hardware acceleration. A popular architecture for DNN acceleration, adopted by the Google Tensor Processing Unit (TPU), utilizes a s…
View article: Improved Trajectory Planning for On-Road Self-Driving Vehicles Via Combined Graph Search, Optimization & Topology Analysis
Improved Trajectory Planning for On-Road Self-Driving Vehicles Via Combined Graph Search, Optimization & Topology Analysis Open
Trajectory planning is an important component of autonomous driving. It takes the result of route-level navigation plan and generates the motion-level commands that steer an autonomous passenger vehicle (APV). Prior work on solving this pr…
View article: BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Open
Deep learning-based techniques have achieved state-of-the-art performance on a wide variety of recognition and classification tasks. However, these networks are typically computationally expensive to train, requiring weeks of computation o…
View article: SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud Open
Inference using deep neural networks is often outsourced to the cloud since it is a computationally demanding task. However, this raises a fundamental issue of trust. How can a client be sure that the cloud has performed inference correctl…
View article: On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability
On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability Open
View article: Shelang : An Implementation of Probabilistic Programming Language and its Applications
Shelang : An Implementation of Probabilistic Programming Language and its Applications Open
Nowadays, probabilistic models are playing a significant role in various areas in- cluding machine learning, artificial intelligence and cognitive science, etc. How- ever, as those models are becoming more and more complex, it shows that t…