
Deep learning
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The problem of reducing traffic congestion on highways is one of the conundrums that the transport industry as well as the government would like to solve. In this article, we apply the Double Deep Q-Network (DDQN) algorithm to a multi-agent model of traffic congestion and compare it with two other algorithms.
8p
vimitsuki
06-05-2025
0
0
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Efficient water resource management is a critical mandate for governmental authorities, as it directly impacts the effective utilization of this invaluable natural resource. The expeditious and accurate extraction of water surfaces significantly impacts governmental decision-making.
9p
vimitsuki
06-05-2025
0
0
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Đề cương cung cấp các kiến thức cơ bản trong lĩnh vực máy học đồng thời tiếp cận các hướng tiếp cận máy học hiện đại như thuật toán học sâu (Deep Learning) để ứng dụng giải quyết một số bài toán trong thực tế. Qua môn học này sinh viên có thể hiểu và cài đặt được kiến trúc mạng Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) với các framework nổi tiếng như Tensorflow và Pytorch.
9p
bachlapkim01
09-05-2025
1
1
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Luận văn Thạc sĩ Hệ thống thông tin "Phát triển Chatbot trên nền tảng Transformers ứng dụng trong tìm kiếm, tra cứu thông tin về trường Đại học Công nghệ Đông Á" được nghiên cứu với mục tiêu: Tìm hiểu và trình bày các khái niệm cơ bản về Chatbot; các kỹ thuật về Deep learning, mô hình Transformers. Khảo sát, đánh giá hiện trạng, nhu cầu truy cập, tìm hiểu và hỏi đáp thông tin về Trường Đại học Công nghệ Đông Á với các giải pháp đang được sử dụng.
70p
vinarutobi
06-05-2025
1
1
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This study presents a novel polyp segmentation approach using ResUnet++. Trained on Kvasir-SEG and CVCClinicDB, ResUnet++ significantly outperforms traditional UNet and ResUnet. Its residual blocks and attention mechanisms enhance feature extraction, leading to improved segmentation in challenging cases.
9p
visarada
28-04-2025
0
0
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In this article, we will discuss the use of a database, called Churn Modeling, which collects statistical data from banks. We will also explore the application of the BernoulliNB algorithm, combined with the incremental machine learning method, to process streaming data and analyze and predict customer churn rates in banks.
10p
visarada
28-04-2025
0
0
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The present study aims to explore the utilization of a depression symptom database, employing classical machine learning techniques, with a focus on the Random Forest algorithm alongside other methodologies, to assess and diagnose stress levels.
12p
visarada
28-04-2025
0
0
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The research focuses on applying deep learning to automate the fruit recognition and classification process, meeting the development needs of modern agriculture. Applying this technology helps improve efficiency and classification quality and reduces labor costs, resulting in lower product prices. The research team used two deep learning models, SSD300 and YOLOv10s, to recognize and classify six types of fruits: apples, bananas, kiwis, lemons, oranges, and strawberries.
9p
vimaito
11-04-2025
0
0
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In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.
8p
viling
11-10-2024
1
1
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In this paper, we used Convolution neural network (CNN) that exploits the visual properties of the input data to obtain features from network traffic, thereby achieving good intrusion detection performance.
11p
viling
11-10-2024
3
1
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The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.
7p
viengfa
28-10-2024
2
2
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This paper investigates the impact of word embedding techniques on enhancing SMS spam detection models. Traditional statistical methods (BoW, TF-IDF) are compared with advanced techniques (Word2Vec, fastText, GloVe, PhoBERT) using a proprietary dataset.
5p
viengfa
28-10-2024
4
2
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In this paper, we propose an effective AMC using deep learning (DL) for flexible and adaptive OFDM-based optical networks. The proposed DL-based AMC is able to classify four typical modulation schemes such as binary phase-shift keying (BPSK), quadrature PSK (QPSK), 8-PSK, and 16- quadrature amplitude modulation (QAM) in dynamic network conditions.
6p
viengfa
28-10-2024
3
2
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In this article, we establish a Digital Radio over Fiber (DRoF) information system with two wireless channels utilizing two advanced phase modulation techniques, namely Differential Phase Shift Keying (DPSK), for the CRAN connection and investigate parameters related to nonlinearity such as refractive index n2.
6p
viengfa
28-10-2024
4
2
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This paper is structured as follows. The following section presents related work. Section 3 summarizes the characteristics of the two datasets utilized in the model and the system’s overall architecture for image-based disease diagnosis. Section 4 provides our experimental results that compare the performance metrics with other studies.
6p
viengfa
28-10-2024
3
2
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This study proposes to test a combination model between CNN network and XGBoost algorithm for weather image classification problem. The proposed model uses deep learning network, namely CNN for feature extraction, then feeds the features into the XGBoost classifier to recognize the images.
6p
viengfa
28-10-2024
1
1
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Despite certain advancements achieving high accuracy, current methods still require substantial improvements to be applicable in practical scenarios. Diverging from text detection in images/videos, this paper addresses the issue of text detection within license plates by amalgamating multiple frames of distinct perspectives.
10p
viengfa
28-10-2024
6
2
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Artificial intelligence is gradually emerging as a method for optimizing various tasks, offering cost-saving and highly efficient solutions. Nowadays, Al is used as a general term for diverse tasks performed by computers. Fields like machine learning, deep learning, and data science, among others within this scope, are considered part of Al as long as they exhibit the characteristics of artificial intelligence.
12p
viuzumaki
28-03-2025
3
1
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Bài giảng "Máy học nâng cao: Python, jupyter notebook, kaggle" cung cấp cho người đọc các nội dung: Cài đặt Python 3 và IDE Pycharm, jupyter notebook, dịch vụ hỗ trợ deep learning và machine learning, kaggle datasets. Mời các bạn cùng tham khảo nội dung chi tiết.
48p
myhouse06
24-03-2025
9
2
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Bài giảng "Máy học nâng cao: Deep learning - An introduction" cung cấp cho người đọc các nội dung: Introduction, applications, convolutional neural networks vs. recurrent neural networks, hardware and software. Mời các bạn cùng tham khảo nội dung chi tiết.
109p
myhouse06
24-03-2025
4
1
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