Search alternatives:
detecting algorithm » detection algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
detect » detected (Expand Search)
detecting » detecteding (Expand Search)
detecting algorithm » detection algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
detect » detected (Expand Search)
detecting » detecteding (Expand Search)
-
41
Plant disease detection using drones in precision agriculture
Published 2023“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
-
42
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Therefore, this study aims to evaluate several versions of Recurrent Neural Networks (RNNs) and Feedforward Neural Networks (FNNs) for detecting cyberbullying in the Arabic language. Although these algorithms are widely used in text classification and outperform the performance of classical classifiers, many have been extensively investigated in other domains such as sentiment analysis and dialect identification, as well as cyberbullying detection in English text. …”
Get full text
-
43
Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem
Published 2016“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
Get full text
Get full text
Get full text
Get full text
article -
44
Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
Published 2024“…As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. There are many machine-learning and deep-learning algorithms have been developed by researchers. …”
-
45
Cutting‐edge technologies for detecting and controlling fish diseases: Current status, outlook, and challenges
Published 2024“…Here, we highlighted the potential of machine learning algorithms in early pathogen detection and the possibilities of intelligent aquaculture in controlling disease outbreaks at the farm level. …”
-
46
Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Cyberbullying can negatively impact stakeholders and can vary from psychological to pathological, such as self-isolation, depression and anxiety potentially leading to suicide. Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. …”
Get full text
-
47
Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Cyberbullying can negatively impact stakeholders and can vary from psychological to pathological, such as self-isolation, depression and anxiety potentially leading to suicide. Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. …”
Get full text
Get full text
-
48
An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
Published 2019“…Also, it is possible that the attack is not directly detected. Hence, this highlights the need for an algorithm that is capable of assessing the widespread damage scale before starting the repair of the inconsistent medical database. …”
Get full text
Get full text
Get full text
masterThesis -
49
-
50
Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysis
Published 2025“…We also apply machine learning algorithms to establish a baseline for deepfake detection on this dataset, contributing to the detection of fraudulent sign language videos.…”
Get full text
article -
51
Efficient XML Structural Similarity Detection using Sub-tree Commonalities
Published 2007“…Developing efficient techniques for comparing XML-based documents becomes essential in the database and information retrieval communities. Various algorithms for comparing hierarchically structured data, e.g. …”
Get full text
Get full text
conferenceObject -
52
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
Get full text
-
53
-
54
YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm
Published 2025“…This study introduces an improved PCB defect detection model, YOLO-DefXpert, using the YOLOv11 algorithm to address the low accuracy and efficiency challenges in detecting tiny-sized defects on PCBs. …”
-
55
A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …”
-
56
Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
Published 2006“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
Get full text
Get full text
Get full text
conferenceObject -
57
-
58
IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture
Published 2025“…The IntruSafe combines FCNN and LSTM to ensure the detection of both malicious text and image data. It detects and simultaneously protects the IoMT network from further intrusion with only a 0.18% service interruption rate. …”
-
59
A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…Then, the DRF optimization algorithm is applied to optimally tune the features required for accurate intrusion detection and classification. …”
-
60