自传
发表于 2025-3-30 10:27:57
Vision-Based Human Activity Recognition Methods Using Pose Estimationnput the pose is used in different formats. The analysis carried out shows how the numerical simplification of the inputs facilitates learning compared to a “human” approach (which, on the contrary, could consider it easier to start from the graphic visualization of the skeleton).
Bmd955
发表于 2025-3-30 12:53:25
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硬化
发表于 2025-3-30 18:12:20
A Synthetic Dataset for Learning Optical Flow in Underwater Environmentwater environment is considered, due to sudden changes in lighting, water turbidity, movements of the background, particles, and other objects. In this perspective, our work presents a synthetic dataset of underwater scenes, endowed with optical flow labels, to demonstrate the benefits of training a
BLA
发表于 2025-3-30 21:54:32
BERT Classifies SARS-CoV-2 Variantshe virus to quickly recognize its variant. The selected model BERT is a transformer-based neural network first developed for natural language processing. Nonetheless, it has been effectively used in numerous applications, such as genomic sequence analysis. Thus, the fine-tuning of BERT was performed
Esalate
发表于 2025-3-31 04:43:42
https://doi.org/10.1007/978-3-531-90937-0m. Cardiologists manually measured 24 features per ECG. Then, a multi-layer perceptron (MLP), a boosted decision tree (BDT) model, a decision tree, a Support Vector Machine (SVM), and a Naïve Bayes (NB) classifier were employed to classify the ECGs. All models show a high negative predictive value:
FIR
发表于 2025-3-31 07:34:59
Empirische Analyse sozialer Problemeion. The foremost is related to adopting a convolutional neural network (faster R-CNN) with a pre-training on a very large dataset, it was possible to employ the transfer learning (TL) technique. The main benefits of TL include: speed up training considerably, saving of resources, improving the effi
厌倦吗你
发表于 2025-3-31 11:53:29
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AFFIX
发表于 2025-3-31 16:56:58
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顽固
发表于 2025-3-31 21:15:04
Empirische Analyse sozialer Probleme a more robust and larger training set, i.e., the .15,700 labeled light curves from the NASA’s Kepler survey. We then used the learned representation as basic knowledge and fine-tuned the CNN upper layers by making them task dependent on the TESS labeled samples. Moreover, we use the dropout and ada
Kidney-Failure
发表于 2025-3-31 21:58:19
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