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Deep neural network
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Severe air pollution in Vietnam's tourism areas has become a significant economic issue in recent years. While many studies have found a link between population exposure to air pollution and poor health outcomes, short-term exposure to air pollutants in high-pollution zones can result in acute health consequences; thus, poor air quality jeopardizes visitors' health and well-being and threatens the tourism industry's sustainability.
14p
viyamanaka
06-02-2025
2
2
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This paper presents initial experiments on using deep learning to identify pulmonary diseases through X-ray image recognition. In experiments, there were three pulmonary diseases: aortic enlargement, lung opacity, and another lesion.
9p
tuetuebinhan000
23-01-2025
2
1
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Short-term prediction of regional energy consumption by metaheuristic optimized deep learning models
Modern civilization is heavily dependent on energy, which burdens the energy sector. Therefore, a highly accurate energy consumption forecast is essential to provide valuable information for efficient energy distribution and storage. This study proposed a hybrid deep learning model, called I-CNN-JS, by incorporating a jellyfish search (JS) algorithm into an ImageNetwinning convolutional neural network (I-CNN) to predict weekahead energy consumption.
6p
vibenya
31-12-2024
6
2
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This review explores recent ML advancements in assessing corrosion in RC structures. Various algorithms, such as Artificial Neural Networks (ANNs), Gene Expression Programming (GEP), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM) and Ensemble Learning, have shown potential in estimating corrosion processes, predicting material properties, and evaluating structural durability.
7p
vibenya
31-12-2024
5
2
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Bài giảng "Máy học nâng cao: Deep learning an introduction" cung cấp cho người học các kiến thức: Introduction, applications, convolutional neural networks and recurrent neural networks, hardware and software. Mời các bạn cùng tham khảo nội dung chi tiết.
109p
abcxyz123_08
11-04-2020
53
6
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This thesis develops a flexible customer behavior analysis system, including essential head pose estimation or F-formation modules. This system will be evaluated in an actual retail store. Further, after studying the system, realizing the mentioned problems of the head pose problem, we also propose a process to collect the head pose dataset and multi-task deep neural network model, fusing face detection and head pose estimation to yield face position and head pose at the same time.
72p
khanhchi0912
12-04-2024
7
2
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The research project deals with two different types of data for two separate analysis. The first analysis deals with normalised RNA-seq breast cancer data where machine learning techniques are used to classify and identify the biomarker of cancer. Second analysis deals with raw DNA methylated leukemia samples to determine the mutations.
102p
runthenight04
02-02-2023
8
4
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Mục tiêu nghiên cứu của luận văn là vận dụng kiến thức đã học để xây dựng một hệ thống trả lời tự động, sử dụng mạng học sâu Deep Neural Networks, dựa trên khung làm việc sequence-to-sequence và cơ chế attention để sinh ra câu trả lời tự động từ một chuỗi đầu vào tương ứng. Mô hình được huấn luyện end-to-end GNMT (Google’s Neural Machine Translation) trên tập dữ liệu miền mở có sẵn.
72p
matroinho2510
08-11-2022
56
16
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Research Aims: The thesis aims to develop deep neural networks for analyzing security data. These techniques improve the accuracy of machine learning-based models applied in NAD. Therefore, the thesis attempts to address the above challenging problems in NAD using models and techniques in deep neural networks. Specifically, the following problems are studied.
128p
armyofthedead
23-06-2021
17
3
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With Europe’s ageing fleet of nuclear reactors operating closer to their safety limits, the monitoring of such reactors through complex models has become of great interest to maintain a high level of availability and safety.
9p
christabelhuynh
29-05-2020
10
1
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Luận văn đặt ra mục tiêu nghiên cứu các mô hình có thể phát sinh văn bản, sử dụng các mạng học sâu Deep Neural Networks, dựa trên khung làm việc sequence-to-sequence, để huấn luyện trên tập dữ liệu câu hỏi và trả lời tại trường Đại học Công nghiệp Hà Nội. Từ đó xây dựng, cài đặt và vận hành một mô hình trả lời tự động với mục tiêu của đề tài là tiết kiệm được nhân lực và thời gian trong quá trình tiếp nhận, và giải quyết các yêu cầu của học sinh - sinh viên trong trường.
18p
hanh_tv27
06-04-2019
60
5
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