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Traditional detective
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This research undertakes a comparative analysis of lane detection methodologies, explicitly focusing on traditional image processing techniques and Convolutional Neural Networks (CNNs). The evaluation utilized a sample of 500 images from the CULane dataset, which encompasses a diverse range of traffic scenarios.
14p
vithomson
02-07-2024
0
0
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The study sheds light on the role of word embeddings in constructing robust spam detection models, offering valuable guidance for model selection. The methodology, comparative analysis, and future directions are also presented in the paper.
5p
vithomson
02-07-2024
0
0
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This paper addresses the challenge of fault detection in Wireless Sensor Networks (WSNs), commonly used in fields like environmental monitoring and healthcare. WSNs, prone to various faults due to their deployment in unpredictable environments, require effective solutions for fault detection. Traditional machine learning approaches show limitations such as unsuitability for streaming data and the detection of a single fault type.
10p
visergeyne
18-06-2024
1
0
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Onco-proteogenomics aims to understand how changes in a cancer’s genome influences its proteome. One challenge in integrating these molecular data is the identification of aberrant protein products from massspectrometry (MS) datasets, as traditional proteomic analyses only identify proteins from a reference sequence database.
12p
vioraclene
31-03-2024
6
2
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Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease.
20p
vioraclene
31-03-2024
7
1
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This approach can be problematic because SDN networks have different characteristics than traditional computer systems. In this paper, we propose a new method for SDN intrusion detection using machine learning. Our method addresses the problem of data imbalance, which is a common problem with machine learning datasets.
14p
vigojek
02-02-2024
3
1
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This study introduces an approach to detect deepfake images using transfer learning methods, including XceptionNet, RestNet101, InceptionResV2, MobileNetv2, VGG19 and DenseNet121, along with comparing it with a traditional CNN model.
8p
vigrab
02-02-2024
6
3
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Ebook "Molecular techniques in food biology: Safety, biotechnology, authenticity and traceability" explores all aspects of microbe-food interactions, especially as they pertain to food safety. Traditional morphological, physiological, and biochemical techniques for the detection, differentiation, and identification of microorganisms have severe limitations. As an alternative, many of those responsible for monitoring food safety are turning to molecular tools for identifying foodborne microorganisms.
475p
lamquandat
28-12-2023
8
2
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Outbreaks of the Southern rice black-streaked dwarf virus (SRBSDV) have caused significant losses in many rice-growing areas in Vietnam, especially in both North and Central Vietnam in recent years. To detect the virus, traditional reverse transcription polymerase chain reaction (RT-PCR) methodology and immunoassays are currently employed. RT-PCR is accurate but requires expensive chemicals and instruments, as well as complex procedures that limit its applicability for field tests.
8p
viengels
25-08-2023
5
2
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This paper proposes a Convolutional Neural Network (CNN)- based detection model for website defacements. The model is an extension of previous models based on traditional supervised machine learning techniques and its aims are to improve the detection rate and reduce the false alarm rate.
12p
viannee
02-08-2023
5
4
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Rice is one of the most important food crops in the world and mainly cultivated in paddy feld by transplanting seedlings. However, increasing water scarcity due to climate change, labor cost for transplanting, and competition from urbanization is making this traditional method of rice production unsustainable in the long term.
14p
vinarcissa
21-03-2023
4
1
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Mineral oil hydrocarbons are used in the consumer goods sector for the elaboration of a wide range of foods and cosmetics. Traditional methods for determining their levels and composition are time consuming and laborious, besides requiring complex instrumentation.
11p
viginny
23-12-2022
5
2
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In the paper "Building and mining graph databases from biomedical heterogeneous networks", in order to explore the underlying knowledge in heterogeneous network data, we propose an approach to the Neo4J graph database and some graph algorithms such as PageRank, Community detection, and Similarity algorithm. Performing experiments on some heterogeneous data, we have obtained significant results, we can see that the proposed method improves efficiency, increases accuracy, and reduces execution time compared to traditional way of storing data.
9p
runordie3
27-06-2022
23
4
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Bleeding complications in cardiac surgery may lead to increased morbidity and mortality. Traditional blood coagulation tests are not always suitable to detect rapid changes in the patient's coagulation status.
7p
viisaacnewton
26-04-2022
7
1
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Traditional differential expression tools are limited to detecting changes in overall expression, and fail to uncover the rich information provided by single-cell level data sets. We present a Bayesian hierarchical model that builds upon BASiCS to study changes that lie beyond comparisons of means, incorporating built-in normalization and quantifying technical artifacts by borrowing information from spike-in genes.
14p
viaristotle
29-01-2022
14
0
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One challenge facing omics association studies is the loss of statistical power when adjusting for confounders and multiple testing. The traditional statistical procedure involves fitting a confounder-adjusted regression model for each omics feature, followed by multiple testing correction.
18p
viarchimedes
26-01-2022
11
0
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Epigenome-wide association studies (EWAS), which seek the association between epigenetic marks and an outcome or exposure, involve multiple hypothesis testing. False discovery rate (FDR) control has been widely used for multiple testing correction. However, traditional FDR control methods do not use auxiliary covariates, and they could be less powerful if the covariates could inform the likelihood of the null hypothesis.
19p
viarchimedes
26-01-2022
10
1
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Defect detection is recognized to be the most integral criterion for the printed circuit boards (PCBs) quality in industrial manufacturing. The traditional PCB inspection methods have several disadvantages such as time-consuming, labor-intensive, environmental clutter - susceptibility, and inaccurate detection ability. This paper offers a deep learning method for PCB defect detection.
6p
viericschmid
12-01-2022
23
1
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Curculigo orchioides and Curculigo latifolia (Hypoxidaceae) have been widely used as traditional medicines in Indonesia and other Asian countries for antihyperglycemic, aphrodisiac, antioxidant, and antimicrobial treatments. This work aimed to determine the distribution of secretory structures and metabolites. Metabolite profiling approach of the plant organs was determined by UHPLC-QOrbitrap-HRMS.
32p
tudichquannguyet
29-11-2021
11
1
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In the process of post-transcription, microRNAs (miRNAs) are closely related to various complex human diseases. Traditional verification methods for miRNA-disease associations take a lot of time and expense, so it is especially important to design computational methods for detecting potential associations.
15p
viseulgi2711
31-08-2021
6
1
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