Results 11 to 20 of about 225,848 (315)
DP Compress: A Model Compression Scheme for Generating Efficient Deep Potential Models
Journal of Chemical Theory and Computation, 2022 Machine-learning-based interatomic potential energy surface (PES) models are revolutionizing the field of molecular modeling. However, although much faster than electronic structure schemes, these models suffer from costly computations via deep neural networks to predict the energy and atomic forces, resulting in lower running efficiency as compared to
Denghui Lu +6 more
openaire +3 more sources
Modelling compressible multiphase flows [PDF]
ESAIM: Proceedings, 2013 Summary: We give in this paper a short review of some recent achievements within the framework of multiphase flow modeling. We focus first on a class of compressible two-phase flow models, detailing closure laws and their main properties. Next we briefly summarize some attempts to model two-phase flows in a porous region, and also a class of ...
Coquel, Frédéric +5 more
openaire +3 more sources
ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections
IEEE Access, 2022 With the continuous development of neural networks for computer vision tasks, more and more network architectures have achieved outstanding success. As one of the most advanced neural network architectures, DenseNet shortcuts all feature maps to solve ...
Rui-Yang Ju +4 more
doaj +1 more source
Surface Defect Segmentation Algorithm of Steel Plate Based on Geometric Median Filter Pruning
Frontiers in Bioengineering and Biotechnology, 2022 Problems such as redundancy of detection model parameters make it difficult to apply to factory embedded device applications. This paper focuses on the analysis of different existing deep learning model compression algorithms and proposes a model pruning
Zhiqiang Hao +8 more
doaj +1 more source
An Industrial-Grade Solution for Crop Disease Image Detection Tasks
Frontiers in Plant Science, 2022 Crop leaf diseases can reflect the current health status of the crop, and the rapid and automatic detection of field diseases has become one of the difficulties in the process of industrialization of agriculture.
Guowei Dai, Jingchao Fan, Jingchao Fan
doaj +1 more source
Compact Neural Architecture Designs by Tensor Representations
Frontiers in Artificial Intelligence, 2022 We propose a framework of tensorial neural networks (TNNs) extending existing linear layers on low-order tensors to multilinear operations on higher-order tensors.
Jiahao Su +6 more
doaj +1 more source
Sensors, 2022 Nowadays, improving the traffic safety of visually impaired people is a topic of widespread concern. To help avoid the risks and hazards of road traffic in their daily life, we propose a wearable device using object detection techniques and a novel ...
Junjie Shen, Yiwen Chen, Hideyuki Sawada
doaj +1 more source
A Lightweight Graph Neural Network Algorithm for Action Recognition Based on Self-Distillation
Algorithms, 2023 Recognizing human actions can help in numerous ways, such as health monitoring, intelligent surveillance, virtual reality and human–computer interaction. A quick and accurate detection algorithm is required for daily real-time detection. This paper first
Miao Feng, Jean Meunier
doaj +1 more source
Image-Captioning Model Compression [PDF]
Applied Sciences, 2022 Image captioning is a very important task, which is on the edge between natural language processing (NLP) and computer vision (CV). The current quality of the captioning models allows them to be used for practical tasks, but they require both large computational power and considerable storage space.
Viktar Atliha, Dmitrij Šešok
openaire +2 more sources
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
doaj +1 more source