[PDF] Top 20 Detection and Recognition of Text for Dusty Image using Long Short Term Memory
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Detection and Recognition of Text for Dusty Image using Long Short Term Memory
... to dusty weather visibility, blowing sand, floating dust and dust storms occurs in many regions of ...of text have been ...on image text ... See full document
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PICO Element Detection in Medical Text via Long Short Term Memory Neural Networks
... medical text that belong to the four components: Participants/Problem (P), Intervention (I), Comparison (C) and Outcome ...a Long Short-Term Memory (LSTM) neural network based model to ... See full document
9
Detection of Delivery Servers in Online Video Service using Long Short Term Memory Network
... a memory capturing information about what has been calculated so ...as text, genomes, spoken words ...carrying memory forward described mathematically as: ... See full document
12
Robust unspoken Speech (Electroencephalogram) recognition algorithm using Long Short Term Memory –Deep Neural Networks approach
... signal recognition speech generally referred as unspoken speech is one of the most challenging ...autoencoder using hierarchical feature learning ...features. Long short term ... See full document
10
HIERARCHICAL TEXT CLASSIFICATION USING DICTIONARY BASED APPROACH AND LONG-SHORT TERM MEMORY
... of text categorization for the purpose of classifying the text into the appropriate categories based on the textual ...content. Text categorization is useful in a variety of areas such as spam ... See full document
6
Unified Framework For Deep Learning Based Text Classification
... pattern recognition problems. In recent times, it has solved various text mining problems with improved accuracy as compared to pre-existing ...mining, text document classification & clustering ... See full document
5
Anomaly Detection Using Predictive Convolutional Long Short-Term Memory Units
... capture faster motions while smaller transitional kernels capture slower motions [17]. A visualization of the process can be seen below in Figure 6. The size of the convolutional filters in the input-to-hidden and ... See full document
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NCSU SAS WOOKHEE: A Deep Contextual Long Short Term Memory Model for Text Normalization
... entity recognition (Ritter et ...standard text. As an approach to addressing this challenge, text normalization techniques have been widely investigated, rang- ing from extracting domain specific ... See full document
9
Human activity recognition making use of long short term memory techniques
... activity recognition (HAR) is an old ...activity/fitness detection to alert a user on their watch that they are working out and should begin to track this information (Hardwick ... See full document
16
Automated detection of atrial fibrillation using long short term memory network with RR interval signals
... the long-term monitoring of the human heart ...effective long-term monitoring systems allows us to extend the breath of research by investigating a range of different heart diseases, such as ... See full document
18
Dual supervised learning for non-native speech recognition
... speech recognition techniques and methodologies that have been developed recently can work with up to 90–95% accuracy, depending on the dataset and bench- mark test used ...speech recognition systems can ... See full document
10
Classification of result analysis for recognition image using preceptron model & text using adaptive resonance theory 1 algorithmic approaches
... aracter Recognition is developed to identify either printed characters or handwritten characters (Parikh ...pattern recognition that usually deals with the realization of the ted material into human ... See full document
11
Parallelizable Stack Long Short Term Memory
... Stack Long Short-Term Memory (StackL- STM) is useful for various applications such as parsing and string-to-tree neural machine translation, but it is also known to be notori- ously difficult ... See full document
6
Design of Hybrid Algorithm for Fast and Efficient Image Vector Detection and Recognition
... Digital image processing is an important aspect of image recognition ...both image processing and comparison only if we are able to harness the best properties of each ... See full document
5
A Novel Method for Super Imposed Text Extraction in a Sports Video
... Edge detection methods. The connected component methods detect text by extracting the connected components of monotonous colours that obey certain size, shape, and spatial alignment ...the text ... See full document
6
Chinese Relation Classification using Long Short Term Memory Networks
... from text and then fed into a ...just using the basic unit features from each feature space (sequence, syntactic and depen- dency relation) can achieve reasonably good performance, and adding more complex ... See full document
6
Route Intrusion Detection Based on Long Short Term Memory Recurrent Neural Network
... intrusion detection, which was proposed by Stolfo et ...intrusion detection test results are using this data set despite its old age, the data set can provide good comparison for each intrusion ... See full document
8
Nanoionics-Based Three-Terminal Synaptic Device Using Zinc Oxide
... sensor memory b) short term memory (STM) and c) long term memory ...sensory memory is concerned with a perception of touch, smell or a visual pattern that lasts ... See full document
36
NETWORK INTRUSION DETECTION USING DEEP NEURAL NETWORKS
... According to [17], RNNs are considered reduced-size neural networks. In that paper, the author proposes a three layer RNN architecture with 41 features as inputs and four intrusion categories as outputs, and for ... See full document
9
River Flow Forecasting Using Long Short term Memory
... To fix those issues, one of the most effective solutions is to use Long Short-Term Memory (LSTM). Proposed by Sepp Hochreiter and Jürgen Schmidhuber, LSTM models are mainly designed to avoid ... See full document
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