Search Results - (( code classification using algorithm ) OR ( image classification clustering algorithm ))
Search alternatives:
- classification clustering »
- classification using »
- image classification »
- code classification »
- using algorithm »
-
1
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…To overcome this problem, in recent years, researchers obtained some achievements with combination of invariant local features such as Scale Invariant Feature Transform (SIFT) with global feature of leaf images. Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
Get full text
Get full text
Thesis -
2
An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
Get full text
Get full text
Get full text
Article -
3
Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks
Published 2023“…Finally, a hybrid approach of GoogLeNet deep learning algorithm and Convolution Neural Network- Support Vector Machines (CNN-SVM) deep learning is performed to increase the accuracy of tumor classification. …”
Get full text
Get full text
Article -
4
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
Get full text
Get full text
Thesis -
5
Pattern Classification of Human Epithelial Images
Published 2016“…In this project, there are four stages will be used to analyze pattern classification in human epithelial (HEp-2) images. First of all, image enhancement will take part in order to boost efficiency of algorithm by implementing some of the adjustment and filtering technique to increase the visibility of image. …”
Get full text
Get full text
Final Year Project -
6
Efficient classifying and indexing for large iris database based on enhanced clustering method
Published 2018“…The proposed method can be used to perform global search and exhibits quick convergence rate while optimizing the initial clustering centers of the K-means algorithm. From the experimental results, the proposed method was indeed more effective for clustering and classification and outperformed the traditional k-mean algorithm. …”
Get full text
Get full text
Get full text
Article -
7
Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
Published 2008“…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
Get full text
Get full text
Article -
8
Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…The files are allocated in a continuous series of clusters. The ELM algorithm is applied to the DFRWS (2006) dataset and the results show that the combination of the three methods produces 93.46% classification accuracy.…”
Get full text
Article -
9
Classification of JPEG files by using extreme learning machine
Published 2018“…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
Get full text
Get full text
Article -
10
-
11
-
12
Detecting lung cancer region from CT image using meta-heuristic optimized segmentation approach
Published 2022“…An optimal tumor detection requires noise reduced computed tomography (CT) images for pixel classification. In this paper, the butterfly optimization algorithm-based K-means clustering (BOAKMC) method is introduced for reducing CT image segmentation uncertainty. …”
Get full text
Get full text
Get full text
Get full text
Article -
13
Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
Get full text
Get full text
Get full text
Proceeding Paper -
14
-
15
Dense-cluster based voting approach for license plate identification
Published 2018“…This process gives four clusters for the input image. The number of pixels in clusters (dense cluster) and the standard deviation are computed for deriving new hypotheses. …”
Get full text
Get full text
Article -
16
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
Get full text
Get full text
Get full text
Article -
17
Blood cell image segmentation using unsupervised clustering techniques
Published 2009“…The aim of our research is to develop an effective algorithm for segmentation of the blood cell images. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
18
The classification of hunger behaviour of Lates Calcarifer through the integration of image processing technique and k-Nearest Neighbour learning algorithm
Published 2018“…The clustered fish behaviour is then classified through k-Nearest Neighbour (k-NN) learning algorithm. …”
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
19
Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
Published 2015“…The images are collected and analyzed using digital image processing techniques. k-means clustering algorithm is used to segment the image into two separate regions which are fruit and spike regions. …”
Get full text
Get full text
Thesis -
20
A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…This study presents an algorithm for nosologic segmentation of primary brain tumors on Magnetic Resonance Imaging (MRI) brain images. …”
Get full text
Get full text
Thesis
