猛然一拉
发表于 2025-3-25 04:40:24
Image Binarization with Hybrid Adaptive Thresholdsues, local technique gives a result similar to other local techniques, while the hybrid technique gives a result which is not similar to the previous two but is a very effective one. So it is convenient to apply in degraded document image binarization. This technique is compared with other global as
GAVEL
发表于 2025-3-25 11:18:08
BEN-CNN-BiLSTM: A Model of Consequential Document Set Identification of Bengali Textusing the test dataset to calculate recall, precision, F-score, and accuracy. Compared to other standard classification algorithms in Bengali text classification, our proposed BEN-CNN-BiLSTM model achieved 93.94% accuracy. Thus, it can be said that the proposed BEN-CNN-BiLSTM model can be a new docu
问到了烧瓶
发表于 2025-3-25 11:45:56
A Machine Learning Model for Automatic Sleep Staging Based on Single-Channel EEG Signalsd method were superior to those of state-of-the-art methods centered on the different machine learning classifiers. In this paper, automatic sleep data staging was realized, effectively improving the accuracy.
缩减了
发表于 2025-3-25 16:05:20
Deep Learning-Based Prediction of Time-Series Single-Cell RNA-Seq Dataoint is also necessary when data is degradable or missing. Hence, in this work, we have attempted to develop a deep neural network (DNN)-based prediction model for estimating gene expression values in time-series scRNA-seq data. The DNN regressor is capable of estimating data at advanced time-points
Density
发表于 2025-3-25 22:21:29
Stress Analysis Using Machine Learningctive area of research and achieved high performance of models, those were based on signal and speech which were computationally costlier and text-based research work using a state-of-the-art model called the BERT has achieved an f1-score i.e. 80.65%. This project focuses on text-domain and uses ope
AGOG
发表于 2025-3-26 01:42:54
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SLUMP
发表于 2025-3-26 07:47:00
Classification of Kathakali Asamyuktha Hasta Mudras Using Naive Bayes Classifier and Convolutional N
微尘
发表于 2025-3-26 09:16:52
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织物
发表于 2025-3-26 12:47:37
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巫婆
发表于 2025-3-26 18:09:57
978-981-19-6790-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor