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Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steering angle of a self-driving vehicle that is suitable to be applied to embedded automotive technologies with limited performance. Three well-known pre-trained models were compared in this study: AlexNet, ResNet18, and DenseNet121.

Transfer learning was utilized by modifying the final layer of pre-trained models in order to predict the steering angle of the vehicle. Experiments were conducted on the dataset collected from two different tracks. According to the study's findings, ResNet18 and DenseNet121 have the lowest error percentage for steering angle values. Furthermore, the performance of the modified models was evaluated on predetermined tracks. ResNet18 outperformed DenseNet121 in terms of accuracy, with less deviation from the center of the track, while DenseNet121 demonstrated greater adaptability across multiple tracks, resulting in better performance consistency.

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
The Power Enhancement of a Mini-Gas Turbine by Adding Ethanol to the Compressor Inlet Air
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An experimental study is conducted on the utilization of the inlet ethanol injection technique in order to evaluate its impact on the performance of a two-shaft T200D mini-gas turbine engine. The maximum degradation recorded in power output was 32.8% at the climate temperature of 45oC. Nevertheless, at that temperature, adding ethanol with Eth/LPG ratio of 20% by volume brought an enhancement in power output of 19.2% compared to normal LPG run. SFC of the dual-fuel engine ranked a level of 22% higher than that with pure LPG consumption. The overall efficiency suffered a maximum reduction of 14.4% with Eth/LPG fuel ratio of 20%, but when the loading was raised beyond 70% of the engine full load; the efficiency of dual-fuel engi

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
Functional Shift of Present and Past Participles from No-minal Meaning to Adjectival Meaning: Функциональная транспозиция причастий в прилагательное
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This paper tackles in detail the functional shift of parts of speech, such as the shift of a verbal clause to an adjectival clause, along with the types of such a shift. The researcher identified the important features of participles, as well as the concept of participles, adjectives, and their types. Also, the most important changes that affect the participles during such shifts. Further, an exposition is made of the different producers through which a verbal clause is changed into an adjectival one in Russian.

      This type of functional shift in parts of speech is seen as a process of deriving most of the new words in contemporary Russian. Russian is very rich in new words, whether by way of processe

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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Impact of Islamic Financial Inspection Thought on the Development of Inspection and comparing it with Positive Thought: Theoretical Comparative Study
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You Mohammed, you're prophet of God and I'm Gabriel)). With this heavenly call which Mohammed, the messenger of God (may God's mercies be on him), got and when he left Hiraa cave and after getting the aye ((read with your God's name)), a new period of mankind's history started. From that time, the greatest state was established. There was no public treasury and no public financial resources at that time. Abu Baker (God bless him) spent a lot of money to support the costs of the new mission. After Al-Hijra, the bases of establishing the Islamic state were available but it lacked administrative and financial organizing. Therefore the prophet was very keen to find Islamic system which ensures justice and availability of

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Publication Date
Sun Jun 01 2014
Journal Name
University Of Baghdad
New Analytical Methods for Drugs Analysis A Comparative Study
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Four different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazo

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Publication Date
Sat Aug 06 2022
Journal Name
Ijci. International Journal Of Computers And Information
Techniques for DDoS Attack in SDN: A Comparative Study
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