Predicting scenic ratings using deep learning
Predicting Credit Ratings with Statistical Learning Methods
... Credit ratings have two categories: short-term ratings and long-term ...Long-term ratings are the opinions of the relative credit risk of financial obligations with an original maturity of one year ...
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Predicting Survival of Brain Tumor Patients using Deep Learning
... VGG 16 is available in Keras deep learning library for feature extraction and classification. It uses pre-trained weights for feature extraction and classification to train the model and once it is trained ...
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Predicting book sales trend using deep learning framework
... Abstract—A deep learning framework like Generative Adversarial Network (GAN) has gained popularity in recent years for handling many different computer visions related ...images using GAN, the aim is ...
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Predicting online user behaviour using deep learning algorithms
... Further research can include testing on real-time data, and see the per- formance effects on a real-time. However, more work would need to be done on improving time efficiency of the In terms of scalability, the data is ...
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Predicting invasive ductal carcinoma using a Reinforcement Sample Learning Strategy using Deep Learning
... sample learning scheme is ...evaluated using the Digital Database for Mammography Screening ...of using CNN for large-scale feature extraction and classification in medical images, as well as the ...
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Predicting IELTS ratings using vocabulary measures
... The chapter comprises 8 sections which consist of various subsections. I start from providing a definition of formulaic sequences and a discussion of their acquisition, use, teaching and learning and how they can ...
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The potential of deep learning in marketing : insights from predicting conversion with deep learning
... machine learning models a balanced dataset is ...users. Using the full amount of non-converting users would greatly skew the dataset as seen in Delen ...machine learning model can then simply predict ...
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Deep Learning for Predicting Molecular Electronic Properties
... Experiments and Results The neural network models were implemented in Theano 1 to enable the use of graphics processing units (GPUs) to speed up computations. The models were trained on two almost identical machines ...
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Predicting User Intent from Movie Reviews Using Deep Learning Methods
... b) Recurrent Neural Network In recurrent neural network, each movie review will be mapped into a real vector domain using a popular method known as word embedding. In this method the words are encoded as ...
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Predicting Alzheimer's disease progression using multi-modal deep learning approach
... In addition, our method can make full use of available subjects from each modality for training our clas- sifier. This is a huge advantage in the face of data scarcity. As seen in Fig. 2, the number of subjects with CSF ...
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Predicting deep hypnotic state from sleep brain rhythms using deep learning : a data-repurposing approach
... Though results obtained in this study are promis- ing, several limitations need to be addressed in the future study. First, we only used 2 EEG channels (C4/A1 and C3/A2) since the SHHS data set only included these 2 ...
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A deep learning framework for predicting cyber attacks rates
... nonlinearity. Using five real-world datasets, we showed that the framework sig- nificantly outperforms the other prediction approaches in terms of prediction accuracy, which confirms that LSTM cells can indeed ...
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Tiresias: predicting security events through deep learning
... tested using one day or one week of ...trained using one day of data is about ...trained using the data collected by smart routers with an IPS installed and deployed in these routers to protect smart ...
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Tiresias: Predicting Security Events Through Deep Learning
... Tiresias performance. Sections 5 and 6 show the effectiveness of the system. The prediction of a security event in such a complicated environment is an important challenge. Tiresias shows the ability of effectively ...
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A Deep Learning Framework for Predicting Response to Therapy in Cancer
... RNA using Picogreen (Invitrogen, Carlsbad, CA, USA) and quality assessment using a 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA) was performed for each ...prep using TrueSeq RNA Sample Preparation ...
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DESIGNING PARAMETER AGNOSTIC FRAMEWORK FOR PREDICTING DISEASE ONSET USING DEEP LEARNING METHODS
... Figure 10 Using Valx and Additional Layer + LSTM 4. CONCLUSIONS We can see from the results that we can predict the onset while being disease agnostic. The Table1 below shows the precision of the value extraction ...
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Predicting oral malodour based on the microbiota in saliva samples using a deep learning approach
... by using an SVM based on peak areas of terminal restric- tion fragment length polymorphisms (T-RFLPs) of the 16S rRNA gene as data for supervised machine-learning meth- ods ...[10]. Using this ...
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Enhanced Artificial Intelligence System for Diagnosing and Predicting Breast Cancer Using Deep Learning
... Diagnosis in the medical field plays an important role in saving the lives of patients. This is highlighted specially in the cases where early detection of illness is required, such as breast cancer. Employing machine ...
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Predicting Academic Performance of Students from VLE Big Data using Deep Learning Models
... these categories, having an impact on the student performance, are examined. For students outperforming others with distinction, their age, region and disability are observed to be negatively associated with their ...
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Predicting heating demand and sizing a stratified thermal storage tank using deep learning algorithms
... the deep RNN predictions were used as inputs to the optimization ...obtained using the deep RNN predictions and those using the actual demand are comparatively higher for higher tank sizes, as ...
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