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Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…

Deep neural networks (DNNs) have demonstrated remarkable success across a wide range of machine learning tasks. However, determining an effective network architecture, particularly the sizes of the hidden layers, remains a significant challenge and often relies on inefficient trial-and-error experimentation. In this paper, we propose an automated architecture design approach based on structurally adaptive DNNs,…

Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…

Deep Neural Networks (DNNs) prove to be susceptible to synthetically generated samples, so-called adversarial examples. Such adversarial examples aim at generating misclassifications by specifically optimizing input data for a matching perturbation. With the increasing use of deep learning on embedded devices and the resulting use of quantization techniques to compress deep neural networks, it is…

Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…

Determining the best candidates for a certain job rapidly has been one of the most interesting subjects for recruiters and companies due to high costs and times that takes the process. The accuracy of the models, particularly, is heavily influenced by the discriminant variables that are chosen for predicting the candidates scores. This study aims…

Bird watchers and people obsessed with raising and taming birds make a kind of motivation about our subject. It consists of the creation of an Android application called ”Birds Images Predictor” which helps users to recognize nearly 210 endemic bird species in the world. The proposed solution compares the performance of the python script, which…

The use of a battery to power an electrical or electronic system is accompanied by battery management, i.e. a set of measures intended to preserve it for preventative maintenance, thus the cost reduction. This management is generally based on two key parameters, the (remaining useful life) RUL and the (State-of-health) SOH, which relate respectively to…

The main purpose in this work is to explore the fact that chaos, as a biological characteristic in the brain, should be used in an Artificial Neural Network (ANN) system. In fact, as long as chaos is present in brain functionalities, its properties need empirical investigations to show their potential to enhance accuracies in artificial…

Navigation of a moving object (drone, vehicle, robot, and so on) and related localization in unknown scenes is nowadays a challenging subject to be addressed. Typically, different source devices, such as image sensor, Inertial Measurement Unit (IMU), Time of Flight (TOF), or a combination of them can be used to reach this goal. Recently, due…

The deep learning-based URL classification approach using massive observations has been verified especially in the field of phishing attack detection. Various improvements have been achieved through the modeling of character and word sequence of URL based on convolutional and recurrent neural networks, and it has been proven that an ensemble approach of each model has…

The Hamming neural network is an effective tool for solving problems of recognition and classification of objects, the components of which are encoded using a binary bipolar alphabet, and as a measure of the objects’ proximity the difference between the number of identical bipolar components which compared include objects and the Hamming distance between them…

Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…

Programming industrial robots in a real-life environment is a significant task necessary to be dealt with in modern facilities. The “pick up and place” task is undeniably one of the regular robot programming problems which needs to be solved. At the beginning of the “pick and place” task, the position determination and exact detection of…

The use of Unmanned Aerial Vehicle (UAV) can contribute to find solutions and add value to several agricultural problems, favoring thus productivity, better quality control processes and flexible farm management. In addition, the strategies that allow the acquisition and analysis of data from agricultural environments can help optimize current practices such as crop counting. The…

Depth prediction plays a key role in understanding a 3D scene. Several techniques have been developed throughout the years, among which Convolutional Neural Network has recently achieved state-of-the-art performance on estimating depth from a single image. However, traditional CNNs suffer from the lower resolution and information loss caused by the pooling layers. And oversized parameters…

This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…

In grid connected wind turbine (WT) systems, the maximum power point tracking (MPPT) approach has a crucial role in optimizing the wind energy efficiency. To search for the maximum power value of the wind turbine, this contribution proposes a new Maximum Power Point Tracking System (MPPT) for wind turbine related to a permanent magnet synchronous…

Forecasting the gold price movement’s volatility has essential applications in areas such as risk management, options pricing, and asset allocation. The multivariate model is expected to generate more accurate forecasts than univariate models in time series data like gold prices. Multivariate analysis is based on observation and analysis of more than one statistical variable at…

Wireless sensor networks (WSNs) are having large demands in enormous applications for the decade. The main issue in WSNs is estimating the exact location of unknown nodes. All applications are dependent on the location information of unknown nodes in WSNs. Location information of mobile anchor node is used to estimate the location of unknown nodes.…

In this paper we propose an algorithmic approach for Convolutional Neural Network (CNN) for digital watermarking which outperforms the existing frequency domain techniques in all aspects including security along with the criteria in the neural networks such as conditions embedded, and types of watermarking attack. This research addresses digital watermarking in deep neural networks and…

Gender detection and age estimation become an active research area and a very important field today, wish has been widely used in various applications including them: biometrics, social network, Targeted advertising, access control, human-computer interaction, electronic customer, etc. The need to further improve the recognition or classification rate keeps increasing day after day. In this…

The ever-growing technology in mobile smartphones has enabled users to store sensitive and private information; as a result, it required the need for an improved security system. Previous approaches heavily relied on shallow machine learning algorithms that require feature extraction which is time consuming, laborious and can cause, resulting in poor authentication. In this paper,…

Comparing to other types of vehicle accidents, fatality rate of tipped rollover accidents shows significant number. Thus, tripped rollover prevention systems are important in order to keep driver safe. In other hands, different rollover indices are defined to handle the risk. The variable unknown parameters of each index, for instance, current load of the vehicle…

Nowadays, heart diseases cause the maximum death in the world. Also, due to the noticeable increase of heart diseases, studying this field is one of the important matters in medical community. Therefore, this study tries to benefit using information in data base of cardiac arrhythmia and employ arterial intelligent and neural network, in order to…