Results 71 to 80 of about 370,356 (314)
Dynamic slicing for deep neural networks [PDF]
Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020 Program slicing has been widely applied in a variety of software engineering tasks. However, existing program slicing techniques only deal with traditional programs that are constructed with instructions and variables, rather than neural networks that are composed of neurons and synapses.
Ziqi Zhang +4 more
openaire +2 more sources
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
1191402606/Optimised-Neural-Network-Regression-Model: Optimised-Neural-Network-Regression-Model
, 2021 Dataset and source code for the research paper titled: "Optimised deep neural network model to predict asthma exacerbation based on personalised weather triggers"
1191402606
core +1 more source
Concolic testing for deep neural networks [PDF]
Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering, 2018 Concolic testing combines program execution and symbolic analysis to explore the execution paths of a software program. This paper presents the first concolic testing approach for Deep Neural Networks (DNNs). More specifically, we formalise coverage criteria for DNNs that have been studied in the literature, and then develop a coherent method for ...
Youcheng Sun +5 more
openaire +6 more sources
Dual-Precision Deep Neural Network [PDF]
Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Pattern Recognition, 2020 On-line Precision scalability of the deep neural networks(DNNs) is a critical feature to support accuracy and complexity trade-off during the DNN inference. In this paper, we propose dual-precision DNN that includes two different precision modes in a single model, thereby supporting an on-line precision switch without re-training.
Jae Hyun Park 0012 +2 more
openaire +2 more sources
Deep-deep neural network language models.
, 2018 Deep-deep neural network language models.
Sylvester Olubolu Orimaye (5942264) +2 more
core +1 more source
Real-Time Phase-Only Nulling Based on Deep Neural Network With Robustness
IEEE Access, 2019 Phase-only nulling under sidelobe and mainlobe constraints is a problem of interest in array synthesis which is a nonlinear problem without analytical solution.
Zhonghui Zhao +3 more
doaj +1 more source
The human gut microbiome across the life course
FEBS Letters, EarlyView.Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
wiley +1 more source
Operator compression with deep neural networks
Advances in Continuous and Discrete Models, 2022 AbstractThis paper studies the compression of partial differential operators using neural networks. We consider a family of operators, parameterized by a potentially high-dimensional space of coefficients that may vary on a large range of scales. Based on the existing methods that compress such a multiscale operator to a finite-dimensional sparse ...
Kröpfl, Fabian +2 more
openaire +3 more sources
Deep neural network model for group activity recognition using contextual relationship
Engineering Science and Technology, an International Journal, 2019 In this paper, we present contextual relationship-based learning model using deep neural network for recognizing the activities performed by a group of people in a video sequence.
S.A. Vahora, N.C. Chauhan
doaj +1 more source