A Hybrid Algorithm based on Deep Learning and Restricted Boltzmann Machine for Car Semantic Segmentation from Unmanned Aerial Vehicles (UAVs)-based Thermal Infrared Images

designing unmanned aerial vehicle based on neuro-fuzzy systems

در این پایان نامه، کنترل نرو-فازی در پرنده هدایت پذیر از دور (پهپاد) استفاده شده است ابتدا در روش پیشنهادی اول، کنترل کننده نرو-فازی توسط مجموعه اطلاعات یک کنترل کننده pid به صورت off-line آموزش دیده است و در روش دوم یک کنترل کننده نرو-فازی on-line مبتنی بر شناسایی سیستم توسط شبکه عصبی rbf پیشنهاد شده است. سپس کاربرد این کنترل کننده در پهپاد بررسی شده است و مقایسه ای ما بین کنترل کننده های معمو...

Novel Levenberg-Marquardt based learning algorithm for unmanned aerial vehicles

In this paper, a Levenberg-Marquardt inspired sliding mode control theory based adaptation laws are proposed to train an intelligent fuzzy neural network controller for a quadrotor aircraft. The proposed controller is used to control and stabilize a quadrotor unmanned aerial vehicle in the presence of periodic wind gust. A proportional-derivative controller is firstly introduced based on which ...

A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements

Financial statement fraud has increasingly become a serious problem for business, government, and investors. In fact, this threatens the reliability of capital markets, corporate heads, and even the audit profession. Auditors in particular face their apparent inability to detect large-scale fraud, and there are various ways to identify this problem. In order to identify this problem, the majori...

Ontology-Based Deep Restricted Boltzmann Machine

Deep neural networks are known for their capabilities for automatic feature learning from data. For this reason, previous research has tended to interpret deep learning techniques as data-driven methods, while few advances have been made from knowledge-driven perspectives. We propose to design a semantic rich deep learning model from a knowledge driven perspective, by introducing formal semanti...

A Situational Awareness Tool For Unmanned Aerial Vehicles (UAVs)

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles

Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sourc...