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Research on Fault Diagnosis of Rolling Bearing Based on Gramian Angular Field and Lightweight Model. [PDF]
Shen J, Wu Z, Cao Y, Zhang Q, Cui Y.
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This work reports on the actuation behavior of CP‐based polypyrrole/PVdF TYs soaked in electrolyte/ionic liquids and woven actuators where such TYs are integrated. These studies are important toward the creation of on‐body applications such as wearable soft robotics, where textiles offer many advantages such as increased force, integrated electrical ...
Carin Backe +4 more
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Quality Detection and Grading of Rose Tea Based on a Lightweight Model. [PDF]
Ding Z +6 more
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Enhanced tomato detection in greenhouse environments: a lightweight model based on S-YOLO with high accuracy. [PDF]
Sun X.
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Maize plant height automatic reading of measurement scale based on improved YOLOv5 lightweight model. [PDF]
Li J +5 more
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Lightweighting Large Models: A Review of Model Compression Techniques
Haoran Guan, Junhao Lv, Xi Chen, Lei Qi
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APHS-YOLO: A Lightweight Model for Real-Time Detection and Classification of Stropharia Rugoso-Annulata. [PDF]
Liu RM, Su WH.
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Lightweight models for fruits recognition
2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI), 2019Image classification is a well known example of a complex problem that can be tackled using deep learning. In the latest period, convolutional neural networks were successfully applied in order to solve the problem. Moreover, recently, the research directions have been focusing more on developing lightweight models that can still achieve good ...
Mihai Teletin, Lorand Dobai
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Lightweight Business Process Modelling
2010 International Conference on E-Business and E-Government, 2010The Internet and related technologies have created an interconnected world in which we can exchange information easily, process tasks collaboratively, and form communities among users with similar interests. This allows improved efficiency and performance. Allowing business users to model their needs is a trend of business process modelling.
Li Xie, Lai Xu 0001, Paul de Vrieze
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Lightweight Detection Model RM-LFPN-YOLO for Rebar Counting
In this study, we propose a novel lightweight detection model for rebar counting, which is rectified mobilenet lightweight feature pyramid network based on YOLO (RM-LFPN-YOLO).
Wansheng Cheng, Chunwei Li, Yaowen Xu
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