ISSN:
eISSN:
Disciplines
(Field of Science):
- architecture and urban planning (Engineering and Technology)
- automation, electronics, electrical engineering and space technologies (Engineering and Technology)
- information and communication technology (Engineering and Technology)
- safety engineering (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- civil engineering, geodesy and transport (Engineering and Technology)
- mechanical engineering (Engineering and Technology)
- security studies (Social studies)
- management and quality studies (Social studies)
- international relations (Social studies)
- computer and information sciences (Natural sciences)
(Field of Science)
Ministry points: Help
Year | Points | List |
---|---|---|
Year 2024 | 140 | Ministry scored journals list 2024 |
Year | Points | List |
---|---|---|
2024 | 140 | Ministry scored journals list 2024 |
2023 | 140 | Ministry Scored Journals List |
2022 | 140 | Ministry Scored Journals List 2019-2022 |
2021 | 140 | Ministry Scored Journals List 2019-2022 |
2020 | 140 | Ministry Scored Journals List 2019-2022 |
2019 | 140 | Ministry Scored Journals List 2019-2022 |
2018 | 35 | A |
2017 | 35 | A |
2016 | 35 | A |
2015 | 35 | A |
2014 | 30 | A |
2013 | 35 | A |
2012 | 30 | A |
2011 | 30 | A |
2010 | 32 | A |
Model:
Points CiteScore:
Year | Points |
---|---|
Year 2023 | 9.6 |
Year | Points |
---|---|
2023 | 9.6 |
2022 | 12.3 |
2021 | 11 |
2020 | 9 |
2019 | 8 |
2018 | 6.8 |
2017 | 6.3 |
2016 | 6.5 |
2015 | 5.6 |
2014 | 4.9 |
2013 | 4.5 |
2012 | 4.8 |
2011 | 4.4 |
Impact Factor:
Sherpa Romeo:
Papers published in journal
Filters
total: 11
Catalog Journals
Year 2024
-
Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
-
Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
-
Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
Year 2023
-
Instance segmentation of stack composed of unknown objects
PublicationThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
-
Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
-
Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
-
Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
Year 2020
-
Interpretation and modeling of emotions in the management of autonomous robots using a control paradigm based on a scheduling variable
PublicationThe paper presents a technical introduction to psychological theories of emotions. It highlights a usable ideaimplemented in a number of recently developed computational systems of emotions, and the hypothesis thatemotion can play the role of a scheduling variable in controlling autonomous robots. In the main part ofthis study, we outline our own computational system of emotion – xEmotion – designed as a key structuralelement in...
-
Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublicationIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
Year 2017
-
Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
Year 2011
seen 1700 times