scholarly journals A COMPARISON BETWEEN 3D RECONSTRUCTION USING NERF NEURAL NETWORKS AND MVS ALGORITHMS ON CULTURAL HERITAGE IMAGES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 565-570
Author(s):  
F. Condorelli ◽  
F. Rinaudo ◽  
F. Salvadore ◽  
S. Tagliaventi
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
3D Reconstruction ◽  
Structure From Motion ◽  
Point Of View ◽  
Test Cases ◽  
3D Reconstructions ◽  
Cultural Interest ◽  
Technical Discussion ◽  
Interesting Alternative

Abstract. In this research, an innovative comparison between 3D reconstructions obtained by means of Artificial Intelligence, in particular NeRF Neural Networks, and by Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) open-source algorithms is proposed. The 3D reconstruction comparison is performed on two test cases, one of cultural interest, one useful only for technical discussion. It is known that the approaches are traditionally used with different objectives and in different contexts but they can however also be used with similar purpose, i.e., 3D reconstruction. In particular, we were interested in evaluating how NeRF reconstructions are accurate from a metric point of view and how the models obtained from the application of NeRF differ from the model obtained from the classical photogrammetry. By analyzing the results in the considered test cases, we show how NeRF networks, although computationally demanding, can be an interesting alternative or complementary methodology, especially in cases where classical photogrammetric techniques do not allow satisfactory results to be achieved. It is therefore suggested to expand efforts in this direction by exploiting, for example, the numerous improvement proposals of the original NeRF network.

scholarly journals A Practical 3D Reconstruction Method for Weak Texture Scenes

2021 ◽  
Vol 13 (16) ◽  
pp. 3103
Author(s):  
Xuyuan Yang ◽  
Guang Jiang
Keyword(s):  
Deep Learning ◽  
3D Reconstruction ◽  
High Precision ◽  
Structure From Motion ◽  
Learning Algorithms ◽  
Reconstruction Method ◽  
Multiple Views ◽  
Feature Points ◽  
3D Reconstructions ◽  
Pipe Networks

In recent years, there has been a growing demand for 3D reconstructions of tunnel pits, underground pipe networks, and building interiors. For such scenarios, weak textures, repeated textures, or even no textures are common. To reconstruct these scenes, we propose covering the lighting sources with films of spark patterns to “add” textures to the scenes. We use a calibrated camera to take pictures from multiple views and then utilize structure from motion (SFM) and multi-view stereo (MVS) algorithms to carry out a high-precision 3D reconstruction. To improve the effectiveness of our reconstruction, we combine deep learning algorithms with traditional methods to extract and match feature points. Our experiments have verified the feasibility and efficiency of the proposed method.

Art is realized by neural networks and organized by interaction of systemic immunoelements with space

2021 ◽  
Author(s):  
N.V. Panov ◽  
I.B. Komkov ◽  
A.V. Savelyev ◽  
N.A. Loginova
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Martial Arts ◽  
Point Of View ◽  
Universal Principles ◽  
Plane Interaction ◽  
Multi Level ◽  
The Creation ◽  
Viable System ◽  
Organizational Science

The possibility of acquiring and transferring properties through interaction with space is solved in the martial arts of the East (MAE) using the multi-level logic of the system of restrictions. A creative approach to MAE solves the main problem associated with the formation of an individual's personality, and spatial-plane interaction can provide the perception of the required parameters of the system. Therefore, MAE is not only necessary for world art as the latest viable system, but also serves as the foundation for the creation of artificial intelligence (AI). The aim of the research was to analyze the meaning of MAE for art; to show the possibility of obtaining ways of acquiring and transferring properties in art with the aim of consciously influencing recipients. For any kind of art from the point of view of Nikritin's tectonics, which is based on the organizational science of A.A. Bogdanov (tectology) are characterized by universal principles that can be identified in every art. The martial arts of the East (for example, karate) have all the characteristics inherent in art and creativity in general, in which principles can be distinguished that allow them to be combined and actively used in various combinations. The practical use of approaches typical for MAE is possible taking into account the work of feedback, which is based on the possibility of constructing immunized movements, which are important for robotics, including AI, since they do not allow deviations from a given trajectory or assigned tasks.

scholarly journals Quality of Judgment Assessment

2016 ◽  
pp. 96-110
Author(s):  
José Neves ◽  
John Zeleznikow ◽  
Henrique Vicente
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Information Technologies ◽  
Point Of View ◽  
Knowledge Representation And Reasoning ◽  
Formal Framework ◽  
The Social ◽  
Degree Of Confidence

The intersection of Artificial Intelligence and The Law stands for a multifaceted matter, and its effects set the advances on culture, organization, as well as the social matters, when the emergent information technologies are taken into consideration. From this point of view, the weight of formal and informal Conflict Resolution settings should be highlighted, and the use of defective data, information or knowledge must be emphasized. Indeed, it is hard to do it with traditional problem solving methodologies. Therefore, in this work the focus is on the development of decision support systems, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks. It is intended to evaluate the Quality-of-Judgments and the respective Degree-of-Confidence that one has on such happenings.

scholarly journals On the use of INS to improve Feature Matching

2014 ◽  
Vol XL-1 ◽  
pp. 227-232 ◽  
Author(s):  
A. Masiero ◽  
A. Guarnieri ◽  
A. Vettore ◽  
F. Pirotti
Keyword(s):  
3D Reconstruction ◽  
Structure From Motion ◽  
Feature Matching ◽  
Point Of View ◽  
Scale Invariant ◽  
Navigation Algorithm ◽  
Matching Procedure ◽  
Position And Orientation ◽  
Imaging Sensors ◽  
Scale Invariant Feature

The continuous technological improvement of mobile devices opens the frontiers of Mobile Mapping systems to very compact systems, i.e. a smartphone or a tablet. This motivates the development of efficient 3D reconstruction techniques based on the sensors typically embedded in such devices, i.e. imaging sensors, GPS and Inertial Navigation System (INS). Such methods usually exploits photogrammetry techniques (structure from motion) to provide an estimation of the geometry of the scene. <br><br> Actually, 3D reconstruction techniques (e.g. structure from motion) rely on use of features properly matched in different images to compute the 3D positions of objects by means of triangulation. Hence, correct feature matching is of fundamental importance to ensure good quality 3D reconstructions. <br><br> Matching methods are based on the appearance of features, that can change as a consequence of variations of camera position and orientation, and environment illumination. For this reason, several methods have been developed in recent years in order to provide feature descriptors robust (ideally invariant) to such variations, e.g. Scale-Invariant Feature Transform (SIFT), Affine SIFT, Hessian affine and Harris affine detectors, Maximally Stable Extremal Regions (MSER). <br><br> This work deals with the integration of information provided by the INS in the feature matching procedure: a previously developed navigation algorithm is used to constantly estimate the device position and orientation. Then, such information is exploited to estimate the transformation of feature regions between two camera views. This allows to compare regions from different images but associated to the same feature as seen by the same point of view, hence significantly easing the comparison of feature characteristics and, consequently, improving matching. SIFT-like descriptors are used in order to ensure good matching results in presence of illumination variations and to compensate the approximations related to the estimation process.

Using neural networks and artificial intelligence as a modern method of glaucoma diagnosis

2020 ◽  
pp. 27-28
Author(s):  
A.B. Movsisyan ◽  
◽  
A.V. Kuroyedov ◽  
G.A. Ostapenko ◽  
S.V. Podvigin ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Modern Method ◽  
Glaucoma Diagnosis

Актуальность. Определяется увеличением заболеваемости глаукомой во всем мире как одной из основных причин снижения зрения и поздней постановкой диагноза при имеющихся выраженных изменений со стороны органа зрения. Цель. Повысить эффективность диагностики глаукомы на основании оценки диска зрительного нерва и перипапиллярной сетчатки нейросетью и искусственным интеллектом. Материал и методы. Для обучения нейронной сети были выделены четыре диагноза: первый – «норма», второй – начальная глаукома, третий – развитая стадия глаукомы, четвертый – глаукома далеко зашедшей стадии. Классификация производилась на основе снимков глазного дна: область диска зрительного нерва и перипапиллярной сетчатки. В результате классификации входные данные разбивались на два класса «норма» и «глаукома». Для целей обучения и оценки качества обучения, множество данных было разбито на два подмножества: тренировочное и тестовое. В тренировочное подмножество были включены 8193 снимка с глаукомными изменениями диска зрительного нерва и «норма» (пациенты без глаукомы). Стадии заболевания были верифицированы согласно действующей классификации первичной открытоугольной глаукомы 3 (тремя) экспертами со стажем работы от 5 до 25 лет. В тестовое подмножество были включены 407 снимков, из них 199 – «норма», 208 – с начальной, развитой и далекозашедшей стадиями глаукомы. Для решения задачи классификации на «норма»/«глаукома» была выбрана архитектура нейронной сети, состоящая из пяти сверточных слоев. Результаты. Чувствительность тестирования дисков зрительных нервов с помощью нейронной сети составила 0,91, специфичность – 0,93. Анализ полученных результатов работы показал эффективность разработанной нейронной сети и ее преимущество перед имеющимися методами диагностики глаукомы. Выводы. Использование нейросетей и искусственного интеллекта является современным, эффективным и перспективным методом диагностики глаукомы.

Innovative Marketing Strategies for Select E-Commerce Companies in India - A Review.

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Amit Kumar Bhanja ◽  
P.C Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Business Environment ◽  
Marketing Strategies ◽  
Point Of View ◽  
Digital Marketing ◽  
Customer Base ◽  
Innovative Methods ◽  
Online Shoppers ◽  
Drastic Increase

Innovation is the key to opportunities and growth in today’s competitive and dynamic business environment. It not only nurtures but also provides companies with unique dimensions for constant reinvention of the existing way of performance which enables and facilitates them to reach out to their prospective customers more effectively. It has been estimated by Morgan Stanley that India would have 480 million shoppers buying products online by the year 2026, a drastic increase from 60 million online shoppers in the year 2016. E-commerce companies are aggressively implementing innovative methods of marketing their product offerings using tools like digital marketing, internet of things (IoT)and artificial intelligence to name a few. This paper focuses on outlining the innovative ways of marketing that the E-Commerce sector implements in orders to increase their customer base and aims at determining the future scope of this area. A conceptual comparative study of Amazon and Flipkart helps to determine which marketing strategies are more appealing and beneficial for both the customers and companies point of view.

scholarly journals Training Artificial Intelligence Neural Networks to Detect Devices on a Chest X-ray, a Pathway to COVID-19 Testing

2020 ◽  
Vol 112 (5) ◽  
pp. S50
Author(s):  
Zachary Eller ◽  
Michelle Chen ◽  
Jermaine Heath ◽  
Uzma Hussain ◽  
Thomas Obisean ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
X Ray ◽  
Chest X Ray

scholarly journals Lessons from the COVID-19 Pandemic on the Use of Artificial Intelligence in Digital Radiology: The Submission of a Survey to Investigate the Opinion of Insiders

Healthcare ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 331
Author(s):  
Daniele Giansanti ◽  
Ivano Rossi ◽  
Lisa Monoscalco
Keyword(s):  
Artificial Intelligence ◽  
General Purpose ◽  
Point Of View ◽  
General Point ◽  
Thoracic Radiography ◽  
Digital Radiology ◽  
Electronic Survey ◽  
Radiology Technicians ◽  
Medical Radiology ◽  
Great Development

The development of artificial intelligence (AI) during the COVID-19 pandemic is there for all to see, and has undoubtedly mainly concerned the activities of digital radiology. Nevertheless, the strong perception in the research and clinical application environment is that AI in radiology is like a hammer in search of a nail. Notable developments and opportunities do not seem to be combined, now, in the time of the COVID-19 pandemic, with a stable, effective, and concrete use in clinical routine; the use of AI often seems limited to use in research applications. This study considers the future perceived integration of AI with digital radiology after the COVID-19 pandemic and proposes a methodology that, by means of a wide interaction of the involved actors, allows a positioning exercise for acceptance evaluation using a general purpose electronic survey. The methodology was tested on a first category of professionals, the medical radiology technicians (MRT), and allowed to (i) collect their impressions on the issue in a structured way, and (ii) collect their suggestions and their comments in order to create a specific tool for this professional figure to be used in scientific societies. This study is useful for the stakeholders in the field, and yielded several noteworthy observations, among them (iii) the perception of great development in thoracic radiography and CT, but a loss of opportunity in integration with non-radiological technologies; (iv) the belief that it is appropriate to invest in training and infrastructure dedicated to AI; and (v) the widespread idea that AI can become a strong complementary tool to human activity. From a general point of view, the study is a clear invitation to face the last yard of AI in digital radiology, a last yard that depends a lot on the opinion and the ability to accept these technologies by the operators of digital radiology.

Sign in / Sign up

Export Citation Format

Share Document