Log in

Relevant bibliographies by topics / ENet / Journal articles

To see the other types of publications on this topic, follow the link: ENet.

Journal articles on the topic 'ENet'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'ENet.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Yadav, Shital Sanjay, and Anup S. Vibhute. "Emotion Detection Using Deep Learning Algorithm." International Journal of Computer Vision and Image Processing 11, no. 4 (2021): 30–38. http://dx.doi.org/10.4018/ijcvip.2021100103.

Full text

Abstract:

Automatic emotion detection is a prime task in computerized human behaviour analysis. The proposed system is an automatic emotion detection using convolution neural network. The proposed end-to-end CNN is therefore named as ENet. Keeping in mind the computational efficiency, the deep network makes use of trained weight parameters of the MobileNet to initialize the weight parameters of ENet. On top of the last convolution layer of ENet, the authors place global average pooling layer to make it independent of the input image size. The ENet is validated for emotion detection using two benchmark d

APA, Harvard, Vancouver, ISO, and other styles

2

Oh, Dongpin, and Bonggun Shin. "Improving Evidential Deep Learning via Multi-Task Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (2022): 7895–903. http://dx.doi.org/10.1609/aaai.v36i7.20759.

Full text

Abstract:

The Evidential regression network (ENet) estimates a continuous target and its predictive uncertainty without costly Bayesian model averaging. However, it is possible that the target is inaccurately predicted due to the gradient shrinkage problem of the original loss function of the ENet, the negative log marginal likelihood (NLL) loss. In this paper, the objective is to improve the prediction accuracy of the ENet while maintaining its efficient uncertainty estimation by resolving the gradient shrinkage problem. A multi-task learning (MTL) framework, referred to as MT-ENet, is proposed to acco

APA, Harvard, Vancouver, ISO, and other styles

3

Fu, Guang-Hui, Min-Jie Zong, Feng-Hua Wang, and Lun-Zhao Yi. "A Comparison of Sparse Partial Least Squares and Elastic Net in Wavelength Selection on NIR Spectroscopy Data." International Journal of Analytical Chemistry 2019 (August 1, 2019): 1–12. http://dx.doi.org/10.1155/2019/7314916.

Full text

Abstract:

Elastic net (Enet) and sparse partial least squares (SPLS) are frequently employed for wavelength selection and model calibration in analysis of near infrared spectroscopy data. Enet and SPLS can perform variable selection and model calibration simultaneously. And they also tend to select wavelength intervals rather than individual wavelengths when the predictors are multicollinear. In this paper, we focus on comparison of Enet and SPLS in interval wavelength selection and model calibration for near infrared spectroscopy data. The results from both simulation and real spectroscopy data show th

APA, Harvard, Vancouver, ISO, and other styles

4

Salvaggio, Giuseppe, Giuseppe Cutaia, Antonio Greco, et al. "Deep Learning Networks for Automatic Retroperitoneal Sarcoma Segmentation in Computerized Tomography." Applied Sciences 12, no. 3 (2022): 1665. http://dx.doi.org/10.3390/app12031665.

Full text

Abstract:

The volume estimation of retroperitoneal sarcoma (RPS) is often difficult due to its huge dimensions and irregular shape; thus, it often requires manual segmentation, which is time-consuming and operator-dependent. This study aimed to evaluate two fully automated deep learning networks (ENet and ERFNet) for RPS segmentation. This retrospective study included 20 patients with RPS who received an abdominal computed tomography (CT) examination. Forty-nine CT examinations, with a total of 72 lesions, were included. Manual segmentation was performed by two radiologists in consensus, and automatic s

APA, Harvard, Vancouver, ISO, and other styles

5

Hendricks, M. "ENet President's Problem." American Journal of Evaluation 6, no. 1 (1985): 56–57. http://dx.doi.org/10.1177/109821408500600115.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Comelli, Albert, Navdeep Dahiya, Alessandro Stefano, et al. "Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging." Applied Sciences 11, no. 2 (2021): 782. http://dx.doi.org/10.3390/app11020782.

Full text

Abstract:

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation appl

APA, Harvard, Vancouver, ISO, and other styles

7

Abas, Mohamad Ilyas, Syafruddin Syarif, Ingrid Nurtanio, and Zulkifli Tahir. "Comparison of Convolutional Neural Network Methods for the Classification of Maize Plant Diseases." Register: Jurnal Ilmiah Teknologi Sistem Informasi 10, no. 1 (2024): 46–59. http://dx.doi.org/10.26594/register.v10i1.3656.

Full text

Abstract:

The focus of this study is the classification of maize images with common rust, gray leaf spot, blight, and healthy diseases. Various models, including ResNet50, ResNet101, Xception, VGG16, and ENet, were tested for this purpose. The dataset used for corn plant diseases is publicly available, and the data were split into separate sets for training, validation, and testing. After processing the data, the following models were identified: the Xception model epoch with an accuracy of 83.74%, the ResNet model with an accuracy of 97.19% at epoch 8/10, the ResNet101 model with an accuracy of 97.55%

APA, Harvard, Vancouver, ISO, and other styles

8

Katzenmeyer, C. "Final ENet Board Meeting." American Journal of Evaluation 7, no. 1 (1986): 106. http://dx.doi.org/10.1177/109821408600700117.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Katzenmeyer, Conrad. "Final ENet board meeting." Evaluation Practice 7, no. 1 (1986): 106. http://dx.doi.org/10.1016/s0886-1633(86)80085-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Jabbour, Georges, Melanie Henderson, Angelo Tremblay, and Marie Eve Mathieu. "Aerobic Fitness Indices of Children Differed Not by Body Weight Status but by Level of Engagement in Physical Activity." Journal of Physical Activity and Health 12, no. 6 (2015): 854–60. http://dx.doi.org/10.1123/jpah.2013-0337.

Full text

Abstract:

Objective:Moderate-to-vigorous physical activity (MVPA) improves aerobic fitness in children, which is usually assessed by maximal oxygen consumption. However, other indices of aerobic fitness have been understudied.Methods:To compare net oxygen (VO2net), net energy consumption (Enet), net mechanical efficiency (MEnet), and lipid oxidation rate in active and inactive children across body weight statuses.Design:The sample included normal-weight, overweight, and obese children of whom 44 are active (≥30 min of MVPA/d) and 41 are inactive (<30 min of MVPA/d). VO2net, Enet, MEnet and lipid oxid

APA, Harvard, Vancouver, ISO, and other styles

11

Gao, Xiaofei, Qi Lizhe, Ma Chuangjia, and Yunquan Sun. "Research on real-time cloth edge extraction method based on ENet semantic segmentation." Journal of Engineered Fibers and Fabrics 17 (January 2022): 155892502211318. http://dx.doi.org/10.1177/15589250221131890.

Full text

Abstract:

A vision-based sewing trajectory extraction method aims at the difficulty of adaptive generation of sewing trajectory in garment automatic processing. Firstly, the ENet model is improved and the I-ENet semantic segmentation algorithm is proposed; Then, based on the semantic segmentation results, a dynamic edge extraction method based on the GaussMod fitting method is proposed. Based on segmented images, curve fitting, median filtering, and edge-preserving filtering are used. Finally, the Canny operator is used to find the sewing edge trajectory curve. At last, the sewing trajectory curve of th

APA, Harvard, Vancouver, ISO, and other styles

12

Prema, K., and J. Visumathi. "Parallel Mirrors Based Marine Predator Optimization Algorithm with Deep Learning Model for Quality and Shelf-Life Prediction of Shrimp." International Journal of Electrical and Electronics Research 11, no. 2 (2023): 262–71. http://dx.doi.org/10.37391/ijeer.110204.

Full text

Abstract:

Automatic classification and assessment of shrimp freshness plays a major role in aquaculture industry. Shrimp is one of the highly perishable seafood, because of its flavor and excellent nutritional content. Given the high amount of industrial production, determining the freshness of shrimp quickly and precisely is difficult. Instead of using feature-engineering-based techniques, a novel hybrid classification approach is proposed by combining the strength of convolutional neural networks (CNN) and Marine Predators Algorithm (MPA) for shrimp freshness diagnosis. In order to choose the best hyp

APA, Harvard, Vancouver, ISO, and other styles

13

TASSIGNON, MJ. "EBO, ENET and accredited courses." Acta Ophthalmologica 87 (September 2009): 0. http://dx.doi.org/10.1111/j.1755-3768.2009.2372.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Silva, Maguino Santos da, Francisco José Gondim Pitanga, Jorge Medeiros Gomes, Úrsula Paula Renó Soci, and Alex Cleber Improta Caria. "Eletroestimulação e treinamento físico: uma revisão narrativa." Research, Society and Development 9, no. 12 (2020): e4691211528. http://dx.doi.org/10.33448/rsd-v9i12.11528.

Full text

Abstract:

A Eletroestimulação é uma técnica utilizada por profissionais da área da saúde em tratamentos para diversas doenças e treinamentos esportivos. Pode ser aplicada em academias de ginástica, clínicas de fisioterapia e ambientes esportivos como clubes de futebol, corridas, entre outros. Existem diversas nomenclaturas no mercado relacionando a eletroestimulação, mas todas elas são tecnicamente conhecidas como estimulação neuromuscular elétrica transcutânea (ENET). A ENET de corpo inteiro é uma técnica relativamente nova, e entrou no mercado para potencializar o tratamento e treinamento que já eram

APA, Harvard, Vancouver, ISO, and other styles

15

Ahmed, Shouket Abdulrahman, Hazry Desa, Abadal-Salam T. Hussain, and Taha A. Taha. "Implementation of deep neural networks learning on unmanned aerial vehicle based remote-sensing." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 941. http://dx.doi.org/10.11591/ijai.v13.i1.pp941-947.

Full text

Abstract:

Due to efficient and adaptable data collecting, unmanned aerial vehicle (UAV) has been a popular topic in computer vision (CV) and remote sensing (RS) in recent years. Inspiring by the recent success of deep learning (DL), several enhanced object identification and tracking methods have been broadly applied to a variety of UAV-related applications, including environmental monitoring, precision agriculture, and traffic management. In this research, we present efficient neural network (ENet), a unique deep neural network architecture designed exclusively for jobs demanding low latency operation.

APA, Harvard, Vancouver, ISO, and other styles

16

Abdulrahman, Ahmed Shouket, Hazry Desa, Hussain Abadal-Salam T., and Taha Taha A. "Implementation of deep neural networks learning on unmanned aerial vehicle based remote-sensing." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 941–47. https://doi.org/10.11591/ijai.v13.i2.pp941-947.

Full text

Abstract:

Due to efficient and adaptable data collecting, unmanned aerial vehicle (UAV) has been a popular topic in computer vision (CV) and remote sensing (RS) in recent years. Inspiring by the recent success of deep learning (DL), several enhanced object identification and tracking methods have been broadly applied to a variety of UAV-related applications, including environmental monitoring, precision agriculture, and traffic management. In this research, we present efficient neural network (ENet), a unique deep neural network architecture designed exclusively for jobs demanding low latency operation.

APA, Harvard, Vancouver, ISO, and other styles

17

Stefano, Alessandro, and Albert Comelli. "Customized Efficient Neural Network for COVID-19 Infected Region Identification in CT Images." Journal of Imaging 7, no. 8 (2021): 131. http://dx.doi.org/10.3390/jimaging7080131.

Full text

Abstract:

Background: In the field of biomedical imaging, radiomics is a promising approach that aims to provide quantitative features from images. It is highly dependent on accurate identification and delineation of the volume of interest to avoid mistakes in the implementation of the texture-based prediction model. In this context, we present a customized deep learning approach aimed at addressing the real-time, and fully automated identification and segmentation of COVID-19 infected regions in computed tomography images. Methods: In a previous study, we adopted ENET, originally used for image segment

APA, Harvard, Vancouver, ISO, and other styles

18

Zhang, Teng, Shang Gao, Shao-wu Zhang, and Xiao-dong Cui. "m6Aexpress-enet: Predicting the regulatory expression m6A sites by an enet-regularization negative binomial regression model." Methods 226 (June 2024): 61–70. http://dx.doi.org/10.1016/j.ymeth.2024.04.011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Leblanc, N., X. Wan, and P. M. Leung. "Physiological role of Ca(2+)-activated and voltage-dependent K+ currents in rabbit coronary myocytes." American Journal of Physiology-Cell Physiology 266, no. 6 (1994): C1523—C1537. http://dx.doi.org/10.1152/ajpcell.1994.266.6.c1523.

Full text

Abstract:

The properties and function of Ca(2+)-activated K+ (KCa) and voltage-dependent K+ (IK) currents of rabbit coronary myocytes were studied under whole cell voltage-clamp conditions (22 degrees C). Inhibition of KCa by tetraethylammonium chloride (1-10 mM) or charybdotoxin (50-100 nM) suppressed noisy outward rectifying current elicited by 5-s voltage steps or ramp at potentials > 0 mV, reduced the hump of the biphasic ramp current-voltage relation, and shifted by less than +5 mV the potential at which no net steady-state current is recorded (Enet; index of resting membrane potential). Inhibit

APA, Harvard, Vancouver, ISO, and other styles

20

Zhang, Jie, and Mingyuan He. "Methodology for Severe Convective Cloud Identification Using Lightweight Neural Network Model Ensembling." Remote Sensing 16, no. 12 (2024): 2070. http://dx.doi.org/10.3390/rs16122070.

Full text

Abstract:

This study introduces an advanced ensemble methodology employing lightweight neural network models for identifying severe convective clouds from FY-4B geostationary meteorological satellite imagery. We have constructed a FY-4B based severe convective cloud dataset by a combination of algorithms and expert judgment. Through the ablation study of a model ensembling combination of multiple specialized lightweight architectures—ENet, ESPNet, Fast-SCNN, ICNet, and MobileNetV2—the optimal EFNet (ENet- and Fast-SCNN-based network) not only achieves real-time processing capabilities but also ensures h

APA, Harvard, Vancouver, ISO, and other styles

21

Wiedenmann, B. "From ENET to ENETS: A Long Odyssey in the Land of Small and Rare Tumors." Neuroendocrinology 80, no. 1 (2004): 1–2. http://dx.doi.org/10.1159/000080730.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Vemulapalli, Teja Ram Mohan Sai. "Predicting Crop Yields in Indian Agriculture Using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33602.

Full text

Abstract:

Agriculture provides the backbone of India's economy both within and between. The paper below provides a brief insight into the creation of a fresh model is currently in progress to estimate the variability in the crop yields across various regions in India. Via this simple setting-based approach, such parameters as year, district, season and area can be used to predict the amounts of crop outputs for certain years. By employing sophisticated regression techniques, Kernel Ridge, Lasso, and ENet algorithms are used, to improve the yield prediction precision. Additionally, it implies a technique

APA, Harvard, Vancouver, ISO, and other styles

23

Kim, Sangwon, Jaeyeal Nam, and Byoungchul Ko. "Fast Depth Estimation in a Single Image Using Lightweight Efficient Neural Network." Sensors 19, no. 20 (2019): 4434. http://dx.doi.org/10.3390/s19204434.

Full text

Abstract:

Depth estimation is a crucial and fundamental problem in the computer vision field. Conventional methods re-construct scenes using feature points extracted from multiple images; however, these approaches require multiple images and thus are not easily implemented in various real-time applications. Moreover, the special equipment required by hardware-based approaches using 3D sensors is expensive. Therefore, software-based methods for estimating depth from a single image using machine learning or deep learning are emerging as new alternatives. In this paper, we propose an algorithm that generat

APA, Harvard, Vancouver, ISO, and other styles

24

Summers, Lucia, Alyssa N. Shallenberger, John Cruz, and Lawrence V. Fulton. "A Multi-Input Machine Learning Approach to Classifying Sex Trafficking from Online Escort Advertisements." Machine Learning and Knowledge Extraction 5, no. 2 (2023): 460–72. http://dx.doi.org/10.3390/make5020028.

Full text

Abstract:

Sex trafficking victims are often advertised through online escort sites. These ads can be publicly accessed, but law enforcement lacks the resources to comb through hundreds of ads to identify those that may feature sex-trafficked individuals. The purpose of this study was to implement and test multi-input, deep learning (DL) binary classification models to predict the probability of an online escort ad being associated with sex trafficking (ST) activity and aid in the detection and investigation of ST. Data from 12,350 scraped and classified ads were split into training and test sets (80% an

APA, Harvard, Vancouver, ISO, and other styles

25

Kayanan, Manickavasagar, and Pushpakanthie Wijekoon. "Stochastic Restricted LASSO-Type Estimator in the Linear Regression Model." Journal of Probability and Statistics 2020 (March 30, 2020): 1–7. http://dx.doi.org/10.1155/2020/7352097.

Full text

Abstract:

Among several variable selection methods, LASSO is the most desirable estimation procedure for handling regularization and variable selection simultaneously in the high-dimensional linear regression models when multicollinearity exists among the predictor variables. Since LASSO is unstable under high multicollinearity, the elastic-net (Enet) estimator has been used to overcome this issue. According to the literature, the estimation of regression parameters can be improved by adding prior information about regression coefficients to the model, which is available in the form of exact or stochast

APA, Harvard, Vancouver, ISO, and other styles

26

Reyes, Juan Rufino. "Nowcasting domestic liquidity in the Philippines using machine learning algorithms." Philippine Review of Economics 59, no. 2 (2022): 1–40. http://dx.doi.org/10.37907/1erp2202d.

Full text

Abstract:

This study utilizes a number of algorithms used in machine learning to nowcast domestic liquidity growth in the Philippines. It employs regularization (i.e., Ridge Regression, Least Absolute Shrinkage and Selection Operator (LASSO), Elastic Net (ENET)) and tree-based (i.e., Random Forest, Gradient Boosted Trees) methods in order to support the BSP’s current suite of macroeconomic models used to forecast and analyze liquidity. Hence, this study evaluates the accuracy of time series models (e.g., Autoregressive, Dynamic Factor), regularization, and tree-based methods through an expanding window.

APA, Harvard, Vancouver, ISO, and other styles

27

Chen, Feng Qin. "Research on the Network Safety Loophole of Enet." Applied Mechanics and Materials 687-691 (November 2014): 1942–44. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1942.

Full text

Abstract:

With the continuous development and popularization of computer network information technology, many colleges all have set up campus network. At present, campus network has been the important project in college base installation. However, information security issue of campus network would directly affect college to launch various pedagogical practices and refer to students’ individual privacy security issue. This paper has pointed out many safety loopholes existing in university campus network, and attempted to explore improvement measure and corresponding countermeasure of domestic university

APA, Harvard, Vancouver, ISO, and other styles

28

Gburzynski, P., and P. Rudnicki. "A note on the performance of ENET II." IEEE Journal on Selected Areas in Communications 7, no. 3 (1989): 424–27. http://dx.doi.org/10.1109/49.16875.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Bou Zerdan, Morgan, Jeffrey Andrew How, Larissa Alejandra Meyer, Mark Munsell, and Pamela T. Soliman. "Clinicopathological features and survival outcomes in women with endometrial neuroendocrine tumors." Journal of Clinical Oncology 43, no. 16_suppl (2025): 5604. https://doi.org/10.1200/jco.2025.43.16_suppl.5604.

Full text

Abstract:

5604 Background: Endometrial neuroendocrine tumors (ENET) are rare, representing about 0.8% of endometrial cancers. Due to their aggressive nature, they are often diagnosed at an advanced stage with no standardized treatment guidelines. This study provides data on the clinicopathological features and survival outcomes of ENETs. Methods: This IRB-approved retrospective cohort study evaluated patients with ENETs seen at MD Anderson Cancer Center between 1994 and 2024. All patients with a histology-confirmed diagnosis of ENET were included. Descriptive statistics was used to summarize patients’ c

APA, Harvard, Vancouver, ISO, and other styles

30

Natanzon, Yanina, Madalene Earp, Julie M. Cunningham, et al. "Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer." Cancer Informatics 17 (January 1, 2018): 117693511875534. http://dx.doi.org/10.1177/1176935118755341.

Full text

Abstract:

High-grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with copy number alterations, epigenetic processes, and, to a lesser extent, germline variation. We hypothesized that, when summarized at the gene level, tumor methylation and germline genetic variation, alone or in combination, influence tumor gene expression in HGSOC. We used Elastic Net (ENET) penalized regression method to evaluate these associations and adjust for somatic copy number in 3 independent data sets comprising tumors from more than 470 patients. Penalized regre

APA, Harvard, Vancouver, ISO, and other styles

31

Sridhara, Shankarappa, Nandini Ramesh, Pradeep Gopakkali, et al. "Weather-Based Neural Network, Stepwise Linear and Sparse Regression Approach for Rabi Sorghum Yield Forecasting of Karnataka, India." Agronomy 10, no. 11 (2020): 1645. http://dx.doi.org/10.3390/agronomy10111645.

Full text

Abstract:

Sorghum is an important dual-purpose crop of India grown for food and fodder. Prevailing weather conditions during the crop growth period determine the yield of sorghum. Hence, the crop yield forecasting models based on weather parameters will be an appropriate option for policymakers and researchers to develop sustainable cropping strategies. In the present study, six multivariate weather-based models viz., least absolute shrinkage and selection operator (LASSO), elastic net (ENET), principal component analysis (PCA) in combination with stepwise multiple linear regression (SMLR), artificial n

APA, Harvard, Vancouver, ISO, and other styles

32

Ma, Ling, Xiaomao Hou, and Zhi Gong. "Image Segmentation Technology Based on Attention Mechanism and ENet." Computational Intelligence and Neuroscience 2022 (August 4, 2022): 1–8. http://dx.doi.org/10.1155/2022/9873777.

Full text

Abstract:

With the development of today’s society, medical technology is becoming more and more important in people’s daily diagnosis and treatment and the number of computed tomography (CT) images and MRI images is also increasing. It is difficult to meet today’s needs for segmentation and recognition of medical images by manpower alone. Therefore, the use of computer technology for automatic segmentation has received extensive attention from researchers. We design a tooth CT image segmentation method combining attention mechanism and ENet. First, dilated convolution is used with the spatial informatio

APA, Harvard, Vancouver, ISO, and other styles

33

Sanders, J. R. "A Perspective on the Merger of ENet and ERS." American Journal of Evaluation 6, no. 1 (1985): 16–19. http://dx.doi.org/10.1177/109821408500600105.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Li, Qingyu, and Zhenjiang Miao. "Light Corner Based Object Detector with Stacked-ENet Backbones." Journal of Physics: Conference Series 1229 (May 2019): 012040. http://dx.doi.org/10.1088/1742-6596/1229/1/012040.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Bai, Wei. "An ENet Semantic Segmentation Method Combined with Attention Mechanism." Computational Intelligence and Neuroscience 2023 (February 22, 2023): 1–9. http://dx.doi.org/10.1155/2023/6965259.

Full text

Abstract:

Image semantic segmentation is one of the core tasks for computer vision. It is widely used in fields such as unmanned driving, medical image processing, geographic information systems, and intelligent robots. Aiming at the problem that the existing semantic segmentation algorithm ignores the different channel and location features of the feature map and the simple method when the feature map is fused, this paper designs a semantic segmentation algorithm that combines the attention mechanism. First, dilated convolution is used, and a smaller downsampling factor is used to maintain the resoluti

APA, Harvard, Vancouver, ISO, and other styles

36

إسماعيل, بان صباح. "استخدام الويب كاميرا نوع Enet ككاشف لشدة ضوء مصباح الفلورسنت". Journal of Al-Nahrain University Science 12, № 3 (2009): 16–25. http://dx.doi.org/10.22401/jnus.12.3.28.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Intelligence and Neuroscience, Computational. "Retracted: Image Segmentation Technology Based on Attention Mechanism and ENet." Computational Intelligence and Neuroscience 2023 (August 9, 2023): 1. http://dx.doi.org/10.1155/2023/9802601.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Nasiri, Vahid, Ali Asghar Darvishsefat, Hossein Arefi, Verena C. Griess, Seyed Mohammad Moein Sadeghi, and Stelian Alexandru Borz. "Modeling Forest Canopy Cover: A Synergistic Use of Sentinel-2, Aerial Photogrammetry Data, and Machine Learning." Remote Sensing 14, no. 6 (2022): 1453. http://dx.doi.org/10.3390/rs14061453.

Full text

Abstract:

Forest canopy cover (FCC) is an important ecological parameter of forest ecosystems, and is correlated with forest characteristics, including plant growth, regeneration, biodiversity, light regimes, and hydrological properties. Here, we present an approach of combining Sentinel-2 data, high-resolution aerial images, and machine learning (ML) algorithms to model FCC in the Hyrcanian mixed temperate forest, Northern Iran. Sentinel-2 multispectral bands and vegetation indices were used as variables for modeling and mapping FCC based on UAV ground truth to a wider spatial extent. Random forest (RF

APA, Harvard, Vancouver, ISO, and other styles

39

Aschauer, Johannes, and Christoph Marty. "Evaluating methods for reconstructing large gaps in historic snow depth time series." Geoscientific Instrumentation, Methods and Data Systems 10, no. 2 (2021): 297–312. http://dx.doi.org/10.5194/gi-10-297-2021.

Full text

Abstract:

Abstract. Historic measurements are often temporally incomplete and may contain longer periods of missing data, whereas climatological analyses require continuous measurement records. This is also valid for historic manual snow depth (HS) measurement time series, for which even whole winters can be missing in a station record, and suitable methods have to be found to reconstruct the missing data. Daily in situ HS data from 126 nivo-meteorological stations in Switzerland in an altitudinal range of 230 to 2536 m above sea level are used to compare six different methods for reconstructing long ga

APA, Harvard, Vancouver, ISO, and other styles

40

Pintér, Róbert. "A gamer bennük van – Az eNET Internetkutató, az Esportmilla és az Esport1 közös magyar videojátékos és e-sport kutatásának főbb eredményei." Információs Társadalom 18, no. 1 (2018): 107. http://dx.doi.org/10.22503/inftars.xviii.2018.1.7.

Full text

Abstract:

A tanulmány az eNET, Esportmilla és Esport1 videojáték és e-sport kutatásának főbb kutatási eredményeit mutatja be. A két kutatás számos témát felölelt, ezek közül a tanulmány először a videojáték kutatás eredményeit ismertetve kitér arra, hogy mennyien játszanak videojátékkal idehaza és ehhez mik a főbb motivációik. Foglalkozik annak vizsgálatával, hogy a nem játszók körében mennyire elterjedtek a videojátékosokkal kapcsolatos negatív sztereotípiák, illetve milyen a szülők viszonya a témához. Ezt követően bemutatja, hogy min és mit játszanak a játékosok, illetve mekkora az e-sport játékkal já

APA, Harvard, Vancouver, ISO, and other styles

41

Molla, Md Maeen, Md Sifat Hossain, Md Ayub Ali, Md Raqibul Islam, Mst Papia Sultana, and Dulal Chandra Roy. "Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective." PLOS ONE 20, no. 3 (2025): e0314466. https://doi.org/10.1371/journal.pone.0314466.

Full text

Abstract:

Background Sustainable Development Goal 3 (SDG 3), focusing on ensuring healthy lives and well-being for all, holds global significance and is particularly vital for Bangladesh. Neonatal Mortality Rate (NMR), Under-5 Mortality Rate (U5MR), Maternal Mortality Ratio (MMR) and Death Rate Due to Road Traffic Injuries (RTI) are considered responsible indicators of SDG 3 progress in Bangladesh. The objective of the study is to forecast these indicators of Bangladesh up to 2030 and compare these forecasts with predetermined 2030 targets. The data is obtained from the World Bank’s (WB) website. Method

APA, Harvard, Vancouver, ISO, and other styles

42

Moayedi, Hossein, Dieu Tien Bui, Anastasios Dounis, Zongjie Lyu, and Loke Kok Foong. "Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques." Applied Sciences 9, no. 20 (2019): 4338. http://dx.doi.org/10.3390/app9204338.

Full text

Abstract:

The heating load calculation is the first step of the iterative heating, ventilation, and air conditioning (HVAC) design procedure. In this study, we employed six machine learning techniques, namely multi-layer perceptron regressor (MLPr), lazy locally weighted learning (LLWL), alternating model tree (AMT), random forest (RF), ElasticNet (ENet), and radial basis function regression (RBFr) for the problem of designing energy-efficient buildings. After that, these approaches were used to specify a relationship among the parameters of input and output in terms of the energy performance of buildin

APA, Harvard, Vancouver, ISO, and other styles

43

Wang, Yiqin. "Remote Sensing Image Semantic Segmentation Algorithm Based on Improved ENet Network." Scientific Programming 2021 (October 4, 2021): 1–10. http://dx.doi.org/10.1155/2021/5078731.

Full text

Abstract:

A remote sensing image semantic segmentation algorithm based on improved ENet network is proposed to improve the accuracy of segmentation. First, dilated convolution and decomposition convolution are introduced in the coding stage. They are used in conjunction with ordinary convolution to increase the receptive field of the model. Each convolution output contains a larger range of image information. Second, in the decoding stage, the image information of different scales is obtained through the upsampling operation and then through the compression, excitation, and reweighting operations of the

APA, Harvard, Vancouver, ISO, and other styles

44

Agaba, Sara, Chiara Ferré, Marco Musetti, and Roberto Comolli. "Mapping Soil Organic Carbon Stock and Uncertainties in an Alpine Valley (Northern Italy) Using Machine Learning Models." Land 13, no. 1 (2024): 78. http://dx.doi.org/10.3390/land13010078.

Full text

Abstract:

In this study, we conducted a comprehensive analysis of the spatial distribution of soil organic carbon stock (SOC stock) and the associated uncertainties in two soil layers (0–10 cm and 0–30 cm; SOC stock 10 and SOC stock 30, respectively), in Valchiavenna, an alpine valley located in northern Italy (450 km2). We employed the digital soil mapping (DSM) approach within different machine learning models, including multivariate adaptive regression splines (MARS), random forest (RF), support vector regression (SVR), and elastic net (ENET). Our dataset comprised soil data from 110 profiles, with S

APA, Harvard, Vancouver, ISO, and other styles

45

Wang, Zhu, Shuangge Ma, Michael Zappitelli, Chirag Parikh, Ching-Yun Wang, and Prasad Devarajan. "Penalized count data regression with application to hospital stay after pediatric cardiac surgery." Statistical Methods in Medical Research 25, no. 6 (2016): 2685–703. http://dx.doi.org/10.1177/0962280214530608.

Full text

Abstract:

Pediatric cardiac surgery may lead to poor outcomes such as acute kidney injury (AKI) and prolonged hospital length of stay (LOS). Plasma and urine biomarkers may help with early identification and prediction of these adverse clinical outcomes. In a recent multi-center study, 311 children undergoing cardiac surgery were enrolled to evaluate multiple biomarkers for diagnosis and prognosis of AKI and other clinical outcomes. LOS is often analyzed as count data, thus Poisson regression and negative binomial (NB) regression are common choices for developing predictive models. With many correlated

APA, Harvard, Vancouver, ISO, and other styles

46

Li, Hui, Jinyi Li, Bowen Li, Zhengqian Miao, and Shengli Lu. "Design and Implementation of a Lightweight and Energy-Efficient Semantic Segmentation Accelerator for Embedded Platforms." Micromachines 16, no. 3 (2025): 258. https://doi.org/10.3390/mi16030258.

Full text

Abstract:

With the rapid development of lightweight network models and efficient hardware deployment techniques, the demand for real-time semantic segmentation in areas such as autonomous driving and medical image processing has increased significantly. However, realizing efficient semantic segmentation on resource-constrained embedded platforms still faces many challenges. As a classical lightweight semantic segmentation network, ENet has attracted much attention due to its low computational complexity. In this study, we optimize the ENet semantic segmentation network to significantly reduce its comput

APA, Harvard, Vancouver, ISO, and other styles

47

Mastourah Abdulsatar Ahmeedah, Abdelbaset A.Sh Abdalla, and Ahmed M. Mami. "On using the penalized regression estimators to solve the multicollinearity problem." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 2654–64. http://dx.doi.org/10.30574/wjarr.2024.24.1.3265.

Full text

Abstract:

The paper compares coefficient parameter estimation efficiency using penalized regression approaches. Five estimators are employed: Ridge Regression, LASSO regression, Elastic Net (ENET) Regression, Adaptive Lasso (ALASSO) regression, and Adaptive Elastic Net (AENET) regression methods. The study uses a multiple linear regression model to address multicollinearity issues. The comparison is based on average mean square errors (MSE) using simulated data with varying sizes, numbers of independent variables, and correlation coefficients. The results are expected to be useful and will be applied to

APA, Harvard, Vancouver, ISO, and other styles

48

Mastourah, Abdulsatar Ahmeedah, A.Sh Abdalla Abdelbaset, and M. Mami Ahmed. "On using the penalized regression estimators to solve the multicollinearity problem." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 2654–64. https://doi.org/10.5281/zenodo.15064625.

Full text

Abstract:

The paper compares coefficient parameter estimation efficiency using penalized regression approaches. Five estimators are employed: Ridge Regression, LASSO regression, Elastic Net (ENET) Regression, Adaptive Lasso (ALASSO) regression, and Adaptive Elastic Net (AENET) regression methods. The study uses a multiple linear regression model to address multicollinearity issues. The comparison is based on average mean square errors (MSE) using simulated data with varying sizes, numbers of independent variables, and correlation coefficients. The results are expected to be useful and will be applied to

APA, Harvard, Vancouver, ISO, and other styles

49

Deng, Qitian, Xu Li, Peizhou Ni, Honghai Li, and Zhiyong Zheng. "Enet-CRF-Lidar: Lidar and Camera Fusion for Multi-Scale Object Recognition." IEEE Access 7 (2019): 174335–44. http://dx.doi.org/10.1109/access.2019.2956492.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Alimadadi, Ahmad, Ishan Manandhar, Sachin Aryal, Patricia B. Munroe, Bina Joe, and Xi Cheng. "Machine learning-based classification and diagnosis of clinical cardiomyopathies." Physiological Genomics 52, no. 9 (2020): 391–400. http://dx.doi.org/10.1152/physiolgenomics.00063.2020.

Full text

Abstract:

Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical practice. In this study, we hypothesized that machine learning (ML) can be used as a novel diagnostic approach to analyze cardiac transcriptomic data for classifying clinical cardiomyopathies. RNA-Seq data of human left ventricle tissues were collected from 41 DCM patients, 47 ICM patients, and 49 nonfailure controls (NF) and tested using five ML

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!