Results 41 to 50 of about 14,609 (251)
Combine-Net: An Improved Filter Pruning Algorithm
Information, 2021 The powerful performance of deep learning is evident to all. With the deepening of research, neural networks have become more complex and not easily generalized to resource-constrained devices.
Jinghan Wang, Guangyue Li, Wenzhao Zhang
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Absorption Pruning of Deep Neural Network for Object Detection in Remote Sensing Imagery
Remote Sensing, 2022 In recent years, deep convolutional neural networks (DCNNs) have been widely used for object detection tasks in remote sensing images. However, the over-parametrization problem of DCNNs hinders their application in resource-constrained remote sensing ...
Jielei Wang +4 more
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Research on the Correlation Filter Tracking Model Based on the Deep-Pruned Feature Network
Applied Sciences, 2022 Visual tracking is one of the key research fields in computer vision. Based on the combination of correlation filter tracking (CFT) model and deep convolutional neural networks (DCNNs), deep correlation filter tracking (DCFT) has recently become a ...
Honglin Chen, Chunting Li, Chaomurilige
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Applied Sciences, 2022 The success of the convolutional neural network (CNN) comes with a tremendous growth of diverse CNN structures, making it hard to deploy on limited-resource platforms. These over-sized models contain a large amount of filters in the convolutional layers,
Shrutika S. Sawant +5 more
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Global Biased Pruning Considering Layer Contribution
IEEE Access, 2020 Convolutional neural networks (CNNs) have made impressive achievements in many areas, but these successes are limited by storage and computing costs. Filter pruning is a promising solution to accelerate and compress CNNs. Most existing methods for filter
Zheng Huang, Li Li, Hailin Sun
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Filter Pruning via Attention Consistency on Feature Maps
Applied Sciences, 2023 Due to the effective guidance of prior information, feature map-based pruning methods have emerged as promising techniques for model compression. In the previous works, the undifferentiated treatment of all information on feature maps amplifies the ...
Huoxiang Yang +3 more
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SNF: Filter Pruning via Searching the Proper Number of Filters
CoRR, 2021 Convolutional Neural Network (CNN) has an amount of parameter redundancy, filter pruning aims to remove the redundant filters and provides the possibility for the application of CNN on terminal devices. However, previous works pay more attention to designing evaluation criteria of filter importance and then prune less important filters with a fixed ...
Pengkun Liu +4 more
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Compressing Convolutional Neural Networks by Pruning Density Peak Filters
IEEE Access, 2021 With the recent development of GPUs, the depth of convolutional neural networks (CNNs) has increased, and its structure has become complex. Hence, it is challenging to deploy them into a hardware device owing to its immense computational cost and memory ...
Yunseok Jang, Sangyoun Lee, Jaeseok Kim
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A Dynamic Pruning Method on Multiple Sparse Structures in Deep Neural Networks
IEEE Access, 2023 It is well known that significant computational power and a large amount of memory are required for deep neural networks, which makes them difficult to apply in resource-limited environments.
Jie Hu +8 more
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A minimal cellulosome‐like system in Cellulosilyticum lentocellum
FEBS Open Bio, EarlyView.Cellulose‐degrading bacteria typically use cellulosomes, large multi‐enzyme complexes on a scaffold protein. In Cellulosilyticum lentocellum, we characterise a far smaller arrangement, a single scaffold bound to one cellulase through a single cohesin‐dockerin interaction.
John Allan +2 more
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