预兆前
发表于 2025-3-21 18:54:56
书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0460165<br><br> <br><br>书目名称ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0460165<br><br> <br><br>
国家明智
发表于 2025-3-21 20:26:31
MakedonASRDataset - A Dataset for Speech Recognition in the Macedonian Languages paper provides the first publicly available dataset consisting of audio segments and appropriate textual transcription in the Macedonian language. It is appropriately preprocessed and prepared for direct utilization in the automatic speech recognition pipelines. The dataset was created by students
确认
发表于 2025-3-22 03:18:26
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ASSAY
发表于 2025-3-22 05:40:03
Implementation of the Time Series and the Convolutional Vision Transformers for Biological Signal Prtively new transformer architecture for accomplishing this task in the domain of biological signal processing. Several preceding studies of blood pressure estimation solely for PPG signals have had success with CNN and LSTM neural networks. In this study two types of transformer variants are conside
娴熟
发表于 2025-3-22 09:38:53
The Curious Case of Randomness in Deep Learning Models for Heartbeat Classificationsults by more than 15% on the heartbeat classification performance. Furthermore, we address a research question to evaluate the impact level of random values in the initialization of model parameters experimenting on the classification of ventricular heartbeats in electrocardiogram training and eval
贪心
发表于 2025-3-22 14:05:34
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modest
发表于 2025-3-22 18:35:01
A Review of Dew and Edge Computing: Two Sides of a Modern Internet of Things Solutionhe Internet of Things. In this paper, we analyze the requirements of post-cloud architectures to build such a solution, which clarify the main differences between dew and edge computing approaches. The analysis includes energy consumption, communication and processing requirements, latency, and thro
RLS898
发表于 2025-3-22 23:16:46
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充气球
发表于 2025-3-23 05:15:37
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ERUPT
发表于 2025-3-23 06:48:20
Enhancing Knee Meniscus Damage Prediction from MRI Images with Machine Learning and Deep Learning TeMRI) scans. We utilized the MRNet dataset, and processed it with different approaches, using a one-dimensional grayscale, RGB, and segmented images, complemented with features extracted using Histogram of Oriented Gradients (HOG) and Scale-Invariant Feature Transform (SIFT) techniques. Our objective