The computer vision (CV) is an emerging area with sundry promises. This communication encompasses the past development, recent trends and future directions of the CV in the context of deep learning (DL) algorithms-bas...
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In this paper we illustrate unsupervised and supervised learning algorithms that accurately classify the lithological variations in the 3D seismic data. We demonstrate blind source separation techniques such as the pr...
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Static Application Security Testing tools can be used in the industry to analyze and find potential security vulnerabilities in source code, as mandated by several industrial security standards such as the IEC 62.443....
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This have a look at examines using deep learning algorithms for stepped forward accuracy and velocity in real-time facts evaluation in gadget studying. The goal is to offer a comprehensive assessment of recently devel...
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This paper presents work which extends previous corpus-based work on training Machine learning algorithms to perform Prepositional Phrase attachment. Besides recreating others' experiments to see how algorithms...
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This paper presents work which extends previous corpus-based work on training Machine learning algorithms to perform Prepositional Phrase attachment. Besides recreating others' experiments to see how algorithms' performance changes with the number of training examples and using n-fold cross-validation to produce more accurate error rates, we implemented our own vanilla Machine learning algorithms as a comparison. We also had people perform exactly the same task as the Machine learning algorithms to indicate whether the way forward lies in improving Machine learning algorithms or in improving the data sets used to train Machine learning algorithms. The results from all these experiments feed into our other work transforming the Penn TreeBank into a more useful resource for training Machine learning algorithms to do Prepositional Phrase attachment.
Accurately identifying sugarcane diseases is crucial for farmers. This study explores how advanced deep learning models can be used for this task. We compared different models and created a new hybrid model that combi...
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Machine learning is a branch of Artificial Intelligence that predicts several naturally occurring events by training a model with some data and then using unseen data to test it. This paper seeks to analyze the perfor...
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At present, machine learning is quite popular, and tensorflow framework is also very popular. This system takes the plan management system as the practice platform, realizes the data analysis function through the mach...
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A lean layer of tissue on the rear side of the human eye is the retina, and might be impacted by retinal diseases. The most prevalent retinal complication is age-related macular degeneration (AMD), which impairs eyesi...
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The learning rate is analyzed for linear learning algorithms in this paper. In the presence of outliers, the robustness of several linear learning algorithms is given and it is shown that an absolute criterion based l...
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The learning rate is analyzed for linear learning algorithms in this paper. In the presence of outliers, the robustness of several linear learning algorithms is given and it is shown that an absolute criterion based learning algorithm is more robust than the corresponding quadratic criterion based learning algorithm.
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