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Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video …
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Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
AOSR-Net: All-in-One Sandstorm Removal Network
Most existing sandstorm image enhancement methods are based on traditional theory and prior knowledge, which often limit their …
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AOSR-Net: All-in-One Sandstorm Removal Network
Contrastive Latent Space Reconstruction Learning for Audio-Text Retrieval
Cross-modal retrieval (CMR) has been widely applied in a wide range of applications, such as multimedia search engines, recommendation …
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Contrastive Latent Space Reconstruction Learning for Audio-Text Retrieval
A Hierarchy-based Analysis Approach for Blended Learning: A Case Study with Chinese Students
Blended learning is generally defined as the combination of traditional face-to-face learning and online learning. This learning mode …
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An Empirical Study of Attention Networks for Semantic Segmentation
Semantic segmentation is a vital problem in computer vision. Recently, a common solution to semantic segmentation is the end-to-end …
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Research on the Impact of Executive Shareholding on New Investment in Enterprises Based on Multivariable Linear Regression Model
Based on principal-agent theory and optimal contract theory, companies use the method of increasing executives’ shareholding to …
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Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data
With the increasing volume of high-frequency data in the information age, both challenges and opportunities arise in the prediction of …
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EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually …
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EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
Machine Unlearning Methodology base on Stochastic Teacher Network
The rise of the phenomenon of the “right to be forgotten” has prompted research on machine unlearning, which grants data …
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Machine Unlearning Methodology base on Stochastic Teacher Network
Improving Imbalanced Text Classification with Dynamic Curriculum Learning
Recent advances in pre-trained language models have improved the performance for text classification tasks. However, little attention …
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Improving Imbalanced Text Classification with Dynamic Curriculum Learning