DEEP LEARNING-2020


Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network

Malicious URL Detection using Deep Learning
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Malicious Uniform Resource Locator (URL), aka malicious website is a primary mechanism to host unsolicited content, such as spam, malicious advertisements, phishing, drive-by exploits, to name few. There is imperative to detect the malicious URLs in a timely manner

The unreasonable effectiveness of deep learning in artificial intelligence
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Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks to real-world problems have become ubiquitous, our understanding

Is Deep Learning a Game Changer for Marketing Analytics
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Different types of organizations will try to harness the powers of deep learning in their own ways. An automaker might use them to target new customers, revamp the buying process, or fine-tune product features a specific set of buyers will want. It could draw on a sea of relevant

Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees
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The fragility of deep neural networks to adversarially-chosen inputs has motivated the need to revisit deep learning algorithms. Including adversarial examples during training is a popular defense mechanism against adversarial attacks. This mechanism can be formulated

BREAST CANCER SEVERITY PREDICATION USING DEEP LEARNING TECHNIQUES
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Breast cancer is one of the most common types of cancer most often affecting women. It is a leading cause of cancer death in less developed countries. Thus, it is important to characterize the severity of the disease as soon as possible. In this paper, we applied deep

Deep Learning in Ultrasound Imaging
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In this article, we consider deep learning strategies in ultrasound systems, from the front end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on many aspects of ultrasound imaging Human-centric visual analysis is regarded as one of the most fundamental problems in computer vision, which augments human images in a variety of application fields. Developing solutions for comprehensive human-centric visual applications could have Deep learning has entered a period of designing, implementing, and deploying intensive and diverse applications, which are now visible in numerous areas. Successful case studies became a consequence of the prudent, carefully drafted fundamental concept that

Improving Lives of Indebted Farmers Using Deep Learning : Predicting Agricultural Produce Prices Using Convolutional Neural Networks
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Farmer suicides have become an urgent social problem which governments around the world are trying hard to solve. Most farmers are driven to suicide due to an inability to sell their produce at desired profit levels, which is caused by the widespread Deep learning delivers an interesting and conceptually as well as algorithmically state-of-the- art approach to Artificial Intelligence and Intelligent Systems, in general. This paradigm has been applied to numerous areas including machine translation, computer vision, and naturalThis book discusses the state-of-the-art deep learning models used by researchers recently. Various deep architectures and their components are discussed in detail. Algorithms that are used to train deep architectures with fast convergence rate are illustrated with applications The paradigm of deep learning has achieved a wealth of successes, came with a plethora of concepts, methodologies, and ensuing algorithms and applications. Today, we are witnessing visible progress in this dynamically growing area. The growing interest is present

Convective Storm Nowcasting Using a Deep Learning Approach
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Valuable information is contained in meteorological data, which could be used for convective storm nowcasting. For example, by assimilating radial velocity and reflectivity of multiple radars, the convective-scale variational Doppler radar analysis system (VDRAS)

Automating Cyberdeception Evaluation with Deep Learning
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A machine learning -based methodology is proposed and implemented for conducting evaluations of cyberdeceptive defenses with minimal human involvement. This avoids impediments associated with deceptive research on humans, maximizing the efficacy of

When Deep Learning meets Web Measurements to infer Network Performance
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Web browsing remains one of the dominant applications of the internet, so inferring network performance becomes crucial for both users and providers (access and content) so as to be able to identify the root cause of any service degradation. Recent works have proposed

Comparison of semi-automatic and deep learning -based automatic methods for liver segmentation in living liver transplant donors
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PURPOSE We aimed to compare the accuracy and repeatability of emerging machine learning -based (ie, deep learning ) automatic segmentation algorithms with those of well- established interactive semi-automatic methods for determining liver volume in living liver

Biomedical Imaging and Analysis In the Age of Sparsity, Big Data, and Deep Learning
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IMAGING of the human body using a number of different modalities has revolutionized medicine over the past several decades and continues to grow at a rapid pace . More than ever, previously unknown information about biology and disease is being unveiled at a

Deep Learning on the 2-Dimensional Ising Model to Extract the Crossover Region
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The 2-dimensional square Ising model is investigated with a variational autoencoder in the nonvanishing field case for the purpose of extracting the crossover region between the ferromagnetic and paramagnetic phases. The encoded latent variable space is found to Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. Health care informatics and analytics is a new era that brings tremendous opportunities and challenges due to easily

Understanding Privacy Awareness in Android App Descriptions Using Deep Learning
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Permissions are a key factor in Android to protect users privacy. As it is often not obvious why applications require certain permissions, developer-provided descriptions in Google Play and third-party markets should explain to users how sensitive data is processed


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