Results 41 to 50 of about 4,843,262 (245)
Applied Sciences, 2023 Efficient and low-cost modes for detecting metro track geometry defects (TGDs) are essential for condition-prediction-based preventive maintenance, which can help improve the safety of metro operations and reduce the maintenance cost of metro tracks ...
Zhipeng Wang +3 more
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Overview of Differentiable Neural Network Architecture Search
Zhengzhou Daxue xuebao. Gongxue banNeural Architecture Search (NAS) was an interdisciplinary study in the field of deep learning, which aimed to automate the design of neural network structures. NAS required repeated training and evaluation of a large number of candidate networks, which
LU Peng +5 more
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LWMD: A Comprehensive Compression Platform for End-to-End Automatic Speech Recognition Models
Applied Sciences, 2023 Recently end-to-end (E2E) automatic speech recognition (ASR) models have achieved promising performance. However, existing models tend to adopt increasing model sizes and suffer from expensive resource consumption for real-world applications. To compress
Yukun Liu +3 more
doaj +1 more source
Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
DEff-ARTS: differentiable efficient ARchiTecture search
, 2020 Manual design of efficient Deep Neural Networks (DNNs) for mobile and edge devices is an involved process which requires expert human knowledge to improve efficiency in different dimensions. In this paper, we present DEff-ARTS, a differentiable efficient
Merrett, Geoff +3 more
core +1 more source
Unchain the Search Space with Hierarchical Differentiable Architecture Search
, 2021 Differentiable architecture search (DAS) has made great progress in searching for high-performance architectures with reduced computational cost. However, DAS-based methods mainly focus on searching for a repeatable cell structure, which is then stacked
Zhong, Yujie +4 more
core +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Applied Sciences, 2023 In the realm of machine learning, the optimization of hyperparameters and the design of neural architectures entail laborious and time-intensive endeavors.
Jiyong Shin, Kyongseok Park, Dae-Ki Kang
doaj +1 more source
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
IEEE Access, 2023 Mobile devices play a crucial role in human activity recognition as they enable real-time sensing of user interaction for learning algorithms like neural networks.
Won-Seon Lim +3 more
doaj +1 more source