[PDF] Top 20 Use of artificial neural networks in biosensor signal classification
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Use of artificial neural networks in biosensor signal classification
... for signal classifi cation obtained from immobilized acetyl- cholinesterase (AChE) biosensor measurement of organophosphate and carbamate pesticides (Afalon, Methanion, Dithane), that are AChE inhibitors, in ... See full document
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The use of artificial neural networks and other approaches to the classification of common patterns of human movement
... Neural networks can discriminate pathological patterns of human movement and can be used to help clinicians in order to diagnose or assess pathologies. G.[r] ... See full document
262
Classification of Internet traffic using artificial neural networks
... on classification in this manner is yet in its embryonic ...real-time classification and adaptation to changing network ...for classification, ...support classification in these practical ... See full document
10
Network Data Classification through Artificial Neural Networks and GenClust++ Algorithm
... exponential use of internet ...natural use or it may be a malicious one intended to violate the security of the ...combining artificial neural networks and a hybrid clustering algorithm ... See full document
8
Prediction of Stock Prices Using Artificial N...
... addition, artificial neural networks are often able to detect subtle patterns and trends that may be too intricate for humans to ...Further, artificial neural networks can ... See full document
6
Decoding Arm Movements by Myoelectric Signal and Artificial Neural Networks
... digital signal processing verify the validity of its ...peak signal with a maximum voluntary contraction (MVC) performed at least 10 times greater than the mean peak signal muscle at a time of ...the ... See full document
7
On the application and design of artificial neural networks for motor fault detection. II.
... P of the use of artificial neural networks in motor fault detection applications. In Part I1 of this paper, we will discuss how to design an artificial neural network for[r] ... See full document
8
A comparative study of effort estimation techniques using back propagation algorithm
... The use case point (UCP) and function point model has been widely used to estimate software size and ...the use case diagram is ...on artificial neural networks. The neural ... See full document
7
Classification Techniques for Predicting Graduate Employability
... Three classification algorithms, Decision Tree, Support Vector Machines and Artificial Neural Networks are used and being compared for the best ...with classification accuracy of ... See full document
9
An improved bat algorithm with artificial neural networks for classification problems
... Some current examples of metaheuristics are Particle Swarm Optimization (PSO) which has been successfully applied in problems of antenna design (Jin and Rahmat-Samii, 2007) and electro-magnetic (Robinson and ... See full document
62
Correlation analysis and prediction of personality traits using graphic data collections
... social networks are ...automatic classification of graphic information using the apparatus of artificial neural ...investigated, artificial neural networks are used as a ... See full document
7
Intelligent Classification of Supernovae Using Artificial Neural Networks
... The classification of supernovae (explosions of certain stars) divides them into two main types, those of type I do not present Hydrogen in the spectrum while those of type II ...the classification of ... See full document
22
Blind Navigation System using Artificial Intelligence
... CNNs use a multilayer perceptron’s to obtain minimal ...invariant artificial neural networks (SIANN), due to their shared-weight architecture and translation invariance ...convolutional ... See full document
5
HEART ARRHYTHMIA DETECTION AND CLASSIFICATION FROM ECG SIGNAL USING ARTIFICIAL NEURAL NETWORKS
... We use Arrhythmia dataset found on UC-Irvine archive of Machine Learning ...against neural network and various other classification algorithms on jupyter ...of neural network in each ... See full document
6
Extruded bread classification on the basis of acoustic emission signal with application of artificial neural networks
... Artificial neural networks (ANN) are widely used in the field of signal classification (Aslan et ...AE signal analysis as a tool to determine the usefulness of the sound ... See full document
9
ECG Signal Analysis and Classification using Data Mining and Artificial Neural Networks
... disease classification. The proposed method uses Modular neural network (MNN) model to classify arrhythmia into normal and abnormal ...constructed neural network model by varying number of hidden ... See full document
5
Internetworking Indonesia Journal
... a classification method of EEG signal for eye focuses which consists of three eyes movement left, top, and ...of artificial neural network (ANN). Based on the classification results, ... See full document
6
Artificial Neural Network based String Matching Algorithms for Species Classification – A Preliminary Study and Experimental Results
... and neural networks are in ...species classification. In section 3, we will discuss about the use of neural network in ...species classification method in some other ... See full document
9
Assessment of Severity Level for Diabetic Macular Oedema Using Machine Learning Algorithms
... The neural network classifier was employed to assess the severity level of the disease ...probabilistic neural network (PNN) were applied to classify the severity level of diabetic retinopathy ...and ... See full document
8
Enlarging smaller images before inputting into convolutional neural network: zero-padding vs. interpolation
... Since the emergence of CNNs and their staggering success in image classification, many attempts have been made by researchers to improve their accuracy and time per- formance. These improvements have targeted ... See full document
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