Search Results - (( label classification means algorithm ) OR ( java implication based algorithm ))
Search alternatives:
- label classification »
- classification means »
- implication based »
- java implication »
- means algorithm »
-
1
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
Get full text
Get full text
Thesis -
2
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
Get full text
Get full text
Thesis -
3
-
4
Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
Get full text
Get full text
Get full text
Article -
5
VEHICLE CLASSIFICATION USING NEURAL NETWORKS AND IMAGE PROCESSING
Published 2022“…The aim of this study is to propose a vehicle classification scheme where YOLO v5 algorithm and Faster R-CNN algorithm are being implemented separately into vehicle classification, followed by comparison of result between these two algorithms. …”
Get full text
Get full text
Get full text
Article -
6
Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper -
7
Fuzzy C-Means with Improved Chebyshev Distance for Multi-Labelled Data
Published 2018“…Fuzzy C-Means (FCM) is one of the most well-known clustering algorithms, nevertheless its performance has been limited by the utilization of Euclidean as its distance metric.Even though there exist studies that applied FCM with other distance metrics such as Manhattan, Minkowski and Chebyshev, its performance can still be argued particularly on multi-label data.Various applications rely on data points that can be grouped into more than one class and this includes protein function classification and image annotation.This study proposes the employment of FCM that is implement using an improved Chebyshev distance metric.The proposed work eliminates correlation in data points and improve performance of clustering.The results show that the proposed FCM improves the performance of clustering as it produces minimum objective function value and with less iteration count. …”
Get full text
Get full text
Get full text
Article -
8
A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer
Published 2023“…We hypothesized that revealing the implicit meaning of an idiom and using it as a feature may improve the sentiment classification results. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
9
Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
Published 2013Get full text
Get full text
Get full text
Conference or Workshop Item -
10
Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
Published 2013Get full text
Get full text
Get full text
Conference or Workshop Item -
11
AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION
Published 2022“…DenseNet-201 model is proposed as the base network to perform insulator fault detection autonomously. An algorithm with DenseNet-201 backbone consisting of two branches which are class label classification and bounding box regression is developed. …”
Get full text
Get full text
Get full text
Final Year Project Report / IMRAD -
12
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
13
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
14
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For contextual text classification, the pre-trained LLM is further train on classificationspecific labeled data in a process called fine-tuning. …”
Get full text
Get full text
Get full text
Thesis -
15
Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm
Published 2023“…Both the models effectively annotate and predict the leaf disease with good confidence score for each class. The other classification metrics like Precision, F1- score, Mean Average Precision, and recall also shows competitive results. …”
Get full text
Get full text
Get full text
Article -
16
Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…However, the automatic classification of chart images remains a significant challenge, particularly in the absence of labeled data. …”
Get full text
Get full text
Get full text
Article -
17
Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
Get full text
Get full text
Get full text
Get full text
Article -
18
-
19
Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
Get full text
Get full text
Thesis -
20
Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis
