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10 most impressive Research Papers around Artificial Intelligence

Recent research in artificial intelligence

❶When authors co-submit and publish a method article in MethodsX, it appears on ScienceDirect linked to the original research article in this journal. Philosophy has contributed the theories of reasoning and learning, mathematics has given the formal theories:

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Artificial intelligence research paper

Besides, the paper also presents a general method, called feature synthesis, for the fine-to-coarse integration of information from operators at different scales. This helps in establishing the fact that edge detector performance improves considerably as the operator point spread function is extended along the edge.

Minsky, Nathaniel Rochester, Claude E. Shannon, and published in the year This summer research proposal defined the field, and has another first to its name — it is the first paper to use the term Artificial Intelligence.

The paper was authored by Nobuyuki Otsu and published in It has received paper citations so far. Through this paper, Otsu discusses a nonparametric and unsupervised method of automatic threshold selection for picture segmentation. The paper delves into how an optimal threshold is selected by the discriminant criterion to maximize the separability of the resultant classes in gray levels.

The procedure utilizes only the zeroth- and first-order cumulative moments of the gray-level histogram. The method can be easily applied across multi threshold problems. The paper validates the method by presenting several experimental results. This article was co-written by Sergey Ioffe and Christian Szegedy.

The paper received citations and reflects on a HIC score of This is a result of change in parameters of the previous layers. The phenomenon is termed as internal covariate shift. This issue is addressed by normalizing layer inputs.

Batch normalization achieves the same accuracy with 14 times fewer training steps when applied to a state-of-the-art image classification model. In other words, Batch Normalization beats the original model by a significant margin.

Deep Residual Learning for Image Recognition: The authors have delved into residual learning framework to ease the training of deep neural networks that are substantially deeper than those used previously.

Besides, the research paper explicitly reformulates the layers as learning residual functions with reference to the layer inputs, instead of learning unreferenced functions. The research also delves into how comprehensive empirical evidence show that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth. This article was authored by David G. These can be utilized to perform reliable matching between different views of an object or scene.

The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The paper additionally delves into an approach which leverages these features for image recognition.

This approach can help identify objects among clutter and occlusion while achieving near real-time performance.

Deep neural nets with a large number of parameters are very powerful machine learning systems. However, overfitting is a serious problem in such networks. The central premise of the paper is to drop units along with their connections from the neural network during training, thus preventing units from co-adapting too much. This helps in significantly reducing overfitting, while furnishing major improvements over other regularization methods.

Therefore, it is through the use of Ontology Artificial Intelligence which can enable them to limit the damages since the manual process is proved to be time-consuming and expensive to implement. Due to the changes in the trends and mechanisms in which data are handled and managed by various organizations, the acquisition of Ontology Artificial intelligence has proved to be prudent since it ensures that the analysts handle large set of data as fast as possible thus enabling efficient data protection.

According to Callan , during enhancement of cyber security, there are various trends which make the organization to adopt the ontology Artificial Intelligence. Besides, due to the high volume of data which is required to be collected, organized and analyzed, the managers and experts in various fields and departments have shown it wise to adopt the process Callan, According to Margulies , there are various benefits which the Ontology Artificial Intelligence provides to an organization if it is properly integrated and implemented.

These can include the replication of the human decisions, actions and activities without the human errors and does not face the human problems such as emotions, fatigue and limited time Margulies, Besides, it has led to the growth of effectiveness and thinking about the potential risks associated with the advancement in the cyber security attacks in various parts of the world.

Even though it leads to a lot of benefits, there are various challenges which it can still be experienced during its adoption. Besides, there are various difficulties which arise as a result of identifying the insider threats which posits a lot of pressure in an organization. Besides, there is a continuous attack on computers by various virus and malware which manipulate and interfere with the data.

The chapter aims at providing the methods of collecting data, research design, the sampling size and the data analysis procedure. These will be done to provide the users of the information with a chronology of the work and how the research questions are answered so as to meet the objectives of the study.

In this research, the researcher will use quantitative data which will aid in the examination of the secondary collected data that can only be collected in a numerical form. Besides, the research design clasps positivism proposition thus, the researcher gets incessant data from the secondary and primary data.

In this thesis, a random sampling will be used to help in developing discussion for the users hence effectiveness in understanding various variables used. The main source of data for this study will be a secondary data from various journals, books, magazines and articles. The qualitative and quantitative analysis will be used after an efficient collection of data. The statistics will also be abridged to plaid its uniformity, accuracy, consistency and completeness and then arranged to enable coding process Kothari, These thus enhance accuracy and eliminate errors as well as biases which might accrue during data analysis.

The analysis of the secondary data will ensure that there is a valid evidence of how the Ontology Artificial Intelligence Approach influences the cyber security management and control. During the research process, the researcher will ensure that the guidelines as per the data collection, analysis and interpretations are adhered to without a compromise.

Bio-inspiring cyber security and cloud services: Intelligent methods for cyber warfare. Machine Learning in Cyber Trust: Security, Privacy, and Reliability. Harvey Mudd College Type of paper:

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Research Paper on Artificial Intelligence August 24, writer Research Papers 0 Artificial Intelligence or AI is an artificially created intelligence and the name of the branch of mainly computer science that seeks to understand and develop the AI theory and functioning, and tries to build intelligent systems.

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The most downloaded articles from Artificial Intelligence in the last 90 days. Menu. Search. Search. Search in: All. Webpages. Books. it appears on ScienceDirect linked to the original research article in this journal Human-level artificial general intelligence and the possibility of a technological singularity A reaction to Ray.

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JAIR is published by AI Access Foundation, a nonprofit public charity whose purpose is to facilitate the dissemination of scientific results in artificial intelligence. JAIR, established in , was one of the first open-access scientific journals on the Web, and has been a leading publication venue since its inception. Artificial Intelligence This Research Paper Artificial Intelligence and other 64,+ term papers, college essay examples and free essays are available now on Autor: review • December 18, • Research Paper • 2, Words (11 Pages) • 1, Views.4/4(1).

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Artificial intelligence research paper. CHAPTER 1. INTRODUCTION. Introduction. The use of ontology and artificial intelligence in the management and control of cybercrime is in a major increase since it is crucial in handling voluminous data which are very crucial for organizational performance. - This research Paper has problems with formatting ABSTRACT Current neural network technology is the most progressive of the artificial intelligence systems today. Applications of neural networks have made the transition from laboratory curiosities to large, successful commercial applications.