The Exploration of Autonomous Vehicles

2022 ◽  
pp. 930-944
Author(s):  
Anthony J. Gephardt ◽  
Elizabeth Baoying Wang

This chapter explores the world of autonomous vehicles. Starting from the beginning, it covers the history of the automobile dating back to 1769. It explains how the first production automobile came about in 1885. The chapter dives into the history of auto safety, ranging from seatbelts to full-on autonomous features. One of the main focuses is the creation and implementation of artificial intelligent (AI), neural networks, intelligent agents, and deep Learning Processes. Combining the hardware on the vehicle with the intelligence of AI creates what we know as autonomous vehicles today.

Author(s):  
Anthony J. Gephardt ◽  
Elizabeth Baoying Wang

This chapter explores the world of autonomous vehicles. Starting from the beginning, it covers the history of the automobile dating back to 1769. It explains how the first production automobile came about in 1885. The chapter dives into the history of auto safety, ranging from seatbelts to full-on autonomous features. One of the main focuses is the creation and implementation of artificial intelligent (AI), neural networks, intelligent agents, and deep Learning Processes. Combining the hardware on the vehicle with the intelligence of AI creates what we know as autonomous vehicles today.


2021 ◽  
Vol 11 (5) ◽  
pp. 2284
Author(s):  
Asma Maqsood ◽  
Muhammad Shahid Farid ◽  
Muhammad Hassan Khan ◽  
Marcin Grzegorzek

Malaria is a disease activated by a type of microscopic parasite transmitted from infected female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions of the world. Quick diagnosis of this disease will be very valuable for patients, as traditional methods require tedious work for its detection. Recently, some automated methods have been proposed that exploit hand-crafted feature extraction techniques however, their accuracies are not reliable. Deep learning approaches modernize the world with their superior performance. Convolutional Neural Networks (CNN) are vastly scalable for image classification tasks that extract features through hidden layers of the model without any handcrafting. The detection of malaria-infected red blood cells from segmented microscopic blood images using convolutional neural networks can assist in quick diagnosis, and this will be useful for regions with fewer healthcare experts. The contributions of this paper are two-fold. First, we evaluate the performance of different existing deep learning models for efficient malaria detection. Second, we propose a customized CNN model that outperforms all observed deep learning models. It exploits the bilateral filtering and image augmentation techniques for highlighting features of red blood cells before training the model. Due to image augmentation techniques, the customized CNN model is generalized and avoids over-fitting. All experimental evaluations are performed on the benchmark NIH Malaria Dataset, and the results reveal that the proposed algorithm is 96.82% accurate in detecting malaria from the microscopic blood smears.


2021 ◽  
pp. 096372142199033
Author(s):  
Katherine R. Storrs ◽  
Roland W. Fleming

One of the deepest insights in neuroscience is that sensory encoding should take advantage of statistical regularities. Humans’ visual experience contains many redundancies: Scenes mostly stay the same from moment to moment, and nearby image locations usually have similar colors. A visual system that knows which regularities shape natural images can exploit them to encode scenes compactly or guess what will happen next. Although these principles have been appreciated for more than 60 years, until recently it has been possible to convert them into explicit models only for the earliest stages of visual processing. But recent advances in unsupervised deep learning have changed that. Neural networks can be taught to compress images or make predictions in space or time. In the process, they learn the statistical regularities that structure images, which in turn often reflect physical objects and processes in the outside world. The astonishing accomplishments of unsupervised deep learning reaffirm the importance of learning statistical regularities for sensory coding and provide a coherent framework for how knowledge of the outside world gets into visual cortex.


1994 ◽  
Vol 45 (1) ◽  
pp. 92-106
Author(s):  
Hans Henningsen

The View of Nature and History in Grundtvig and LøgstrupBy Hans HenningsenGrundtvig’s and K.E. Løgstrup’s thoughts move in two different dimensions, but with the same intention of demonstrating that it was not the capacity of man to create culture that first gave significance to the world. But where Grundtvig speaks about history, Løgstrup speaks about »phenomena«, »nature«, and »universe«.While Grundtvig was largely unaffected by Kant, the latter - with his concepts of the selfexistent subject and the idea of the faculty of cognition as productive - became a challenge to Løgstrup. Kant heralds an era whose relationship with the universe is characterized as a »marginal existence«. Our culture became an emancipatory culture which was all to the good, but the era lost its sense of the .pre-cultural. structures in which life is »encased«.The era has also emancipated itself from Grundtvig’s historical view. But a history on the premisses of relativism is no history. Or, in Løgstrup’s words, there is no other history than the history of what is essential in life. Therefore, in reality, Løgstrup’s phenomenological and philosophical endeavours become a defence of history. Grundtvig’s view of nature was determined by his radical prioritization of history. He prefers to view nature as part of the historical life of man, which again determines his use of nature images. In Grundtvig there is no religious interpretation of any experience or perception of nature in spite of the fact that everything in the Creation is to be understood as images of the eternal.In Løgstrup there is no such cautions attitude towards nature. Here nature and sense perception are liberating, but as is the case with Grundtvig, nature is seen as the foundation of man’s life, as immediate experience.Grundtvig’s radical prioritization of history colours his view of art. The Creation itself is the greatest work of art; part of it is the upbringing through which all history must be the object of the individual’s own experience. Among the art forms, poetry ranks highest, with the song above all other forms, while Grundtvig only uses disparaging words about painting and sculpture because these art forms are wordless and preclude changes. Løgstrup, however, attaches much greater importance to sense perception and self-recognition through art.These contrasts may be regarded as what Løgstrup calls uniting opposites; it must be remembered, however, that such disparities cannot be harmonized so as to disappear, but are uniting precisely by virtue of the tension that exists between them. The actual existence of the contrasts does not preclude the possibility that in a wider sense the two views may be contained within the same framework and express a common intention.


2007 ◽  
pp. 27-37
Author(s):  
Dmytro V. Tsolin

Every reader of the Old Testament, both experienced researcher and newcomer, cannot fail to pay attention to one peculiarity in the presentation of the idea of ​​God: it is a harmonious (and, at times, amazing) combination of transcendence and immanence. The History of the Creation of the World (Genesis 1: 1 - 2: 3), which begins the first book of the Strictly Testament - Genesis - is an example of an exquisite prose genre with elements of epic poetry. In it, the Creator of the Universe appears to the Almighty, the Wise, and the All-Powerful, standing above the created world: Only one word of it evokes the material world from nothingness. This is emphasized by the repeated use of the formulas אלהים וימר / wa-yyo'mer 'ělohîm ("And Elohim said ...") and ויהי־כן / wa-yəhî khēn ("And so it became"). This use of two narrative constructs at the beginning and at the end of messages about the creative activities of God clearly emphasizes the idea of ​​reconciling the divine Word and being. God is shown here to be transcendental.


2021 ◽  
Vol 6 (5) ◽  
pp. 10-15
Author(s):  
Ela Bhattacharya ◽  
D. Bhattacharya

COVID-19 has emerged as the latest worrisome pandemic, which is reported to have its outbreak in Wuhan, China. The infection spreads by means of human contact, as a result, it has caused massive infections across 200 countries around the world. Artificial intelligence has likewise contributed to managing the COVID-19 pandemic in various aspects within a short span of time. Deep Neural Networks that are explored in this paper have contributed to the detection of COVID-19 from imaging sources. The datasets, pre-processing, segmentation, feature extraction, classification and test results which can be useful for discovering future directions in the domain of automatic diagnosis of the disease, utilizing artificial intelligence-based frameworks, have been investigated in this paper.


Author(s):  
Jay Rodge ◽  
Swati Jaiswal

Deep learning and Artificial intelligence (AI) have been trending these days due to the capability and state-of-the-art results that they provide. They have replaced some highly skilled professionals with neural network-powered AI, also known as deep learning algorithms. Deep learning majorly works on neural networks. This chapter discusses about the working of a neuron, which is a unit component of neural network. There are numerous techniques that can be incorporated while designing a neural network, such as activation functions, training, etc. to improve its features, which will be explained in detail. It has some challenges such as overfitting, which are difficult to neglect but can be overcome using proper techniques and steps that have been discussed. The chapter will help the academician, researchers, and practitioners to further investigate the associated area of deep learning and its applications in the autonomous vehicle industry.


Author(s):  
Rasmita Lenka ◽  
Koustav Dutta ◽  
Ashimananda Khandual ◽  
Soumya Ranjan Nayak

The chapter focuses on application of digital image processing and deep learning for analyzing the occurrence of malaria from the medical reports. This approach is helpful in quick identification of the disease from the preliminary tests which are carried out in a person affected by malaria. The combination of deep learning has made the process much advanced as the convolutional neural network is able to gain deeper insights from the medical images of the person. Since traditional methods are not able to detect malaria properly and quickly, by means of convolutional neural networks, the early detection of malaria has been possible, and thus, this process will open a new door in the world of medical science.


2006 ◽  
Vol 14 (2) ◽  
pp. 241-256 ◽  
Author(s):  
WIM BLOCKMANS

The process of European integration, the complexity of the problems involved and even the resistance it raises, astonishes observers in other parts of the world, especially in large states that have a long history of centralized government behind them. Is there really so little unity in Europe? If so, how can this be explained? Has European diversity generated only problems or has it, in fact, created new and unique opportunities? Is there a chance that growing concerns at EU-level about the cultural dimensions of European citizenship could, in fact, consolidate a sense of community? And, finally, how can historians contribute to the creation of a common European identity, if this is so weakly developed?


2016 ◽  
Vol 3 (1) ◽  
pp. 85-104 ◽  
Author(s):  
Melissa CROUCH

AbstractMyanmar is the only Buddhism-majority country in the world that has developed and maintained a system of family law for Buddhists enforced by the courts. This article considers the construction of Burmese Buddhist law by lawyers, judges, and legislators, and the changes made through legislative intervention in 2015. It begins by addressing the creation and contestation of Burmese Buddhist law to demonstrate that it has largely been defined by men and by its perceived opposites, Hinduism and Islam. Three aspects of Burmese Buddhist law that affect women are then examined more closely. First, Burmese Buddhist law carries no penalties for men who commit adultery, although women may risk divorce and the loss of her property. Second, a man can take more than one wife under Burmese Buddhist law; a woman cannot. Third, restrictions on Buddhist women who marry non-Buddhist men operate to ensure the primacy of Burmese Buddhist law over the potential application of Islamic law. This article deconstructs the popular claim that women are better off under Burmese Buddhist law than under Hindu law or Islamic law by showing how Burmese Buddhist law has been preoccupied with regulating the position of women. The 2015 laws build on this history of Burmese Buddhist law, creating new problems, but also potentially operating as a new source of revenge.


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