[PDF] Top 20 Fingerprint Classification using Artificial Neural Network

Fingerprint Classification using Artificial Neural Network

... of fingerprint is widely used in many applications like identification of ...person. Fingerprint classification is the process of dividing a large amount of fingerprint database within which ... See full document

5

Fingerprint Classification Using Kernel Smoothing Technique and Generalized Regression Neural Network and Probabilistic Neural Network

... both classification and feature extraction [11-13]. Artificial Neural Network (ANN) is another popular method used for classification ...Regression Neural Network (GRNN) ... See full document

6

A Survey on Brain Tumor Classification Using Artificial Neural Network

... Feature Extraction stage is an important stage that uses algorithms and techniques to detect and isolate various desired portions or shapes of a given image .Binarization technique is used in[1] Binarization approach has ... See full document

5

Artificial Neural Network Classification for Gunshot Detection and Localization System

... In Figure 4, the recorded signals from the microphone have undergone a filtering process. A band-pass filter was used to remove unwanted frequencies in the recorded gunshot sound. The filtered signals are fed to the ... See full document

5

Intelligent Neural Network For Bacteria Classification: An Innovation In Artificial Neural Network

... conventional artificial neural network in object ...multiobjects classification, this neural network perform a key role by generating only one decision; whether it would predict ... See full document

8

Glaucoma Recogination Using Superpixel Classification and Artificial Neural Network

... SLIC algorithm is used. SLIC algorithm a is fastest one among super pixel generation. This is used as preprocessing part also. The SLIC algorithm is providing a better way to identify the Glaucoma symptoms before ... See full document

6

Classification of Cancerous Skin using Artificial Neural Network Classifier

... The pre-processing is a modification of the image data that removes unwanted malformations or enhances some image features paramount for further processing. First, the image is resized to adjust images so that it ... See full document

5

CLASSIFICATION OF IRS LISS-III IMAGE USING ARTIFICIAL NEURAL NETWORK

... A classification problem occurs when an object needs to be assigned into a predefined group or class based on a number of observed attributes related to that ...as classification problems. Traditional ... See full document

9

Astrocytoma Type of Brain Tumor Classification using Artificial Neural Network

... and classification system is implemented using ...techniques, artificial neural network and graphical user interface is successfully completed and used in the system to detect and ... See full document

5

NeuroSVM: A Graphical User Interface for Identification of Liver Patients

... learning, Artificial Neural Network, Bagging, Boosting, Naïve Bayes, Kernel-based classifiers, Nearest Neighbour algorithm, Decision Trees, Random Forest, and other ensemble of ... See full document

5

Classification of Mass in Mammograms by Asymmetric Texture Features

... learning artificial neural network is a fundamental technique which is used in CAD systems for the classification of candidate regions as tumorous mass ... See full document

6

Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform

... of neural classification of sputum sounds using wavelet coefficients may help physicians to automatically recognize the sputum deposition of patients with mechanical ventilation in ICU and serve as ... See full document

8

Mitigating Economic Denial of Sustainability (EDoS) in Cloud Environment using Genetic Algorithm and Artificial Neural Network

... and Artificial Neural Network (GANN) for classification of cloud server consumer to minimize the effect of EDoS attacks and will be beneficial to small and medium size ...phases: ... See full document

7

Texture Classification using Artificial Neural Network for Diagnosis of Skin Cancer

... One of the parameters that affect the accuracy of feed forward neural network is the learning rate; it is used to control the rate of weight adjustments. If the value of learning rate is too small then the ... See full document

6

Genome-wide classification of dairy cows using decision trees and artificial neural network algorithms

... the neural networks algorithm to the same groups of SNPs listed in Table 3, and used the same procedure looking for the combination of training-test sets that produced the best ...the neural network ... See full document

12

Prediction of Skin Cancer Using Morphological Neural Network Analysis

... the classification stage involves the combinatorial use of Morphological Image Processing and Artificial Neural Network, called “Morphological Neural Network with Image Pruning” ... See full document

13

Classification of Ovarian Cysts Using Artificial Neural Network

... Marcus Stoetzer, [3] presented Advances in assessing the volume of odontogenic cysts and tumors in the mandible: a retr ospective clinical trial , Head & Face Medicine , 9:14.To compare two methods of creating ... See full document

6

Detection and Classification of Leukaemia using Artificial Neural Network

... An automated system to detect leukaemia cells and classify it into their respective type is designed and created successfully . Images are segmented using k-means segmentation algorithm. Various features are ... See full document

6

PREDICTION AND CLASSIFICATION OF THUNDERSTORMS USING ARTIFICIAL NEURAL NETWORK

... The designed neural network has implemented according to the proposed architecture. It has trained and tested using different weather data. The weights and bias were updated with each iteration. It ... See full document

5

Classification of Robotic Data using Artificial Neural Network

... lattice, speaking to 600 examples of 15 components as we need to order 600 documents into 15 classes. Among the preparation information introduced to the instrument, it puts aside a subset of the preparation information ... See full document

6