Results 21 to 30 of about 226,838 (267)
Roulette: A Pruning Framework to Train a Sparse Neural Network From Scratch
IEEE Access, 2021 Due to space and inference time restrictions, finding an efficient and sparse sub-network from a dense and over-parameterized network is critical for deploying neural networks on edge devices.
Qiaoling Zhong +3 more
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Compression-based Facies Modelling
Mathematical Geosciences, 2023 AbstractSimple object- or pixel-based facies models use facies proportions as the constraining input parameter to be honored in the output model. The resultant interconnectivity of the facies bodies is an unconstrained output property of the modelling, and if the objects being modelled are geometrically representative in three dimensions, commonly ...
Tom Manzocchi +3 more
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A Neural Network Model Compression Approach Based on Deep Feature Map Transfer
IEEE Access, 2020 Neural network is widely used in computer vision. However, with the continuous expansion of the application field, high-precision large parameter neural network model is difficult to deploy on small equipment with limited resources.
Zhibo Guo +4 more
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Modelling Mammographic Compression of the Breast [PDF]
, 2008 We have developed a biomechanical model of the breast to simulate compression during mammographic imaging. The modelling framework was applied to a set of MR images of the breasts of a volunteer. Images of the uncompressed breast were segmented into skin and pectoral muscle, from which a finite element (FE) mesh of the left breast was generated using a
Jae-Hoon Chung +3 more
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To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference [PDF]
2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom), 2018 8 pages, To appear in ISPA ...
Qin, Q +8 more
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IEEE AccessModel Compression is an actively pursued research field in recent years with the goal of deploying state-of-the-art deep neural networks. It is targeted to implementations which are based on power constrained and resource limited devices as the reduced ...
Danhe Tian +2 more
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IEEE Access, 2020 The enormous inference cost of deep neural networks can be mitigated by network compression. Pruning connections is one of the predominant approaches used for network compression.
Sai Aparna Aketi +3 more
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A Modeling of Compressible Droplets in a Fluid [PDF]
Communications in Mathematical Sciences, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boudin, Laurent +2 more
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Frontiers in Plant ScienceIntroductionTimely and accurate recognition of tomato diseases is crucial for improving tomato yield. While large deep learning models can achieve high-precision disease recognition, these models often have a large number of parameters, making them ...
Shuiping Ni +7 more
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Small pre-trained model for background understanding in multi-round question answering
Frontiers in Artificial IntelligenceMulti-round Q&A based on background text needs to infer the answer to the question through the current question, historical Q&A pairs, and background text.
Xin Huang, Hulin Song, Mingming Lu
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