deep learning model
A Survey in Deep Learning Model for Image Annotation
... years, deep learning based image annotation achieves remarkable ...In deep learning models, CNN is mostly used to extract image feature and RNN/LSTM is commonly applied to generate the ...
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Detection of Voids on Concrete Surface Using Deep Learning Model
... of deep learning techniques at detecting voids given photographs of concrete ...proposed deep learning model makes use of a convolutional neural network (CNN) and an artificial neural ...
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Adaptive Deep Learning Model Selection on Embedded Systems
... in deep learning networks (DNNs) make them attractive for embedded ...DNN model to use for a given input, by considering the desired accuracy and inference ...machine learning to develop a ...
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Audio Tagging System using Deep Learning Model
... Abstract: Deep learning has been getting more attention towards the researchers for transforming input data into an effective representation through various learning ...
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A Deep Learning Model of Perception in Color-Letter Synesthesia
... application deep learning to model perception in grapheme-color ...the model learns to accurately create a colored version of the inducing stimulus, according to a statistical distribution ...
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An Efficient Automated Deep Learning Model For Diatom Image Segmentation And Classification
... entire model in the memory. But, the Inception model can be easily tuned indicating that many possible modifications can be done with respect to number of filters in the distinct layers which does not ...
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To Compress, or Not to Compress:Characterizing Deep Learning Model Compression for Embedded Inference
... devices. Model compression techniques can address the computation issue of deep inference on embedded ...how model compression techniques perform across a wide range of ...embedded deep ...
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A Deep Learning Model for Image Classification
... machine learning algorithms uses these extracted features to classify the ...machine learning algorithms have been applied to multilabel image classification problems which have also brought successful ...
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Deep Tweets Analyzer Model for Twitter Mood Visualization and Prediction Based Deep Learning Approach
... a Deep Learning framework for Twitter opinion mining prediction and classification ...the Deep Learning model for Twitter Opinion abstraction and visualization ...visualization ...
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Combining Shallow and Deep Learning for Aggressive Text Detection
... For deep learning models, we tried using a CNN and a BiLSTM network ...each deep learning ...CNN model used a single convolution layer containing 50 filters of width 3 and 30 filters of ...
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Assessing Arabic Weblog Credibility via Deep Co learning
... our deep co- learning approach and the baselines on the testing ...SVM model trained with TF-IDF scores as features has an F1-score of ...supervised deep learning ...fully-supervised ...
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Face Authentication Using Efficient Deep Convolutional Neural Network
... efficient deep Convolutional Neural network (CNN) is proposed to be used for face ...influence model accuracy is demonstrated in this work ...using deep convolutional neural network. Thus, in this ...
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A Probability Density Function Generator Based on Deep Learning
... as activation functions in the hidden layers of the proposed deep learning model for learning actual.. 151[r] ...
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A deep-learning based feature hybrid framework for spatiotemporal saliency detection inside videos
... a deep learning based hybrid spatiotemporal saliency feature extraction framework is proposed for saliency detection from video ...The deep learning model is used for the extraction of ...
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Learning a Deep Hybrid Model for Semi Supervised Text Classification
... the model makes use of a sin- gle labeled sample (taken from an available, small labeled data subset) and an example from either a large unlabeled pool or a ...Layer-wise Learning (BU) The first phase of ...
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A Cognitive Contemplation of Road Accident Predicton Through Deep Learning
... feature variables based on Euclidean metric and utilized k-nearest neighbor method to predict traffic accident [8]. Park collected big traffic accident data of highway in Seoul and build a prediction workflow based on k- ...
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COMPUTATIONALLY EFFICIENT SECURE AND PRIVACY PRESERVING STORAGE OF IMAGE DATA ON HYBRID CLOUD
... though deep learning machine technique having incredible ability in several field such as image processing, natural language processing, speech recognizing, deep learning machine which adopted ...
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A Cloud Computing Fault Detection Method Based on Deep Learning
... of deep learning, depth learning can use a large number of unlabeled data to achieve unsupervised automatic learning [13], through data feature extraction, and then can be used for ...
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Human-level Moving Object Recognition from Traffic Video
... making. Deep learning provides us an effective way to understand big data with a ...a deep neural network is used to semantic tag the recognized ...
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A Classification Model for Severity of Neonatal Jaundice Using Deep Learning
... Machine learning techniques in addition to improvements in available computational control, have come to play a dynamic role in Big Data analytics and knowledge discovery in medical data ...conventional ...
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