GastroNet: A robust attention‐based deep learning and cosine similarity feature selection framework for gastrointestinal disease classification from endoscopic images

MN Noor, M Nazir, I Ashraf, NA Almujally… - CAAI Transactions …, 2023 - Wiley Online Library
Diseases of the Gastrointestinal (GI) tract significantly affect the quality of human life and
have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare …

ReDroidDet: android malware detection based on recurrent neural network

M Almahmoud, D Alzu'bi, Q Yaseen - Procedia Computer Science, 2021 - Elsevier
Android still has the first rank in terms of market share in comparing to other operating
systems. Due to its flexible publishing policy, companies are developing many applications …

An Efficient movie recommendation algorithm based on improved k-clique

P Vilakone, DS Park, K Xinchang, F Hao - Human-centric Computing and …, 2018 - Springer
The amount of movie has increased to become more congested; therefore, to find a movie
what users are looking for through the existing technologies are very hard. For this reason …

Feature selection methods for event detection in Twitter: a text mining approach

AH Hossny, L Mitchell, N Lothian… - Social Network Analysis …, 2020 - Springer
Selecting keywords from Twitter as features to identify events is challenging due to language
informality such as acronyms, misspelled words, synonyms, transliteration and ambiguous …

Filter feature selection methods for text classification: a review

H Ming, W Heyong - Multimedia Tools and Applications, 2024 - Springer
Filter feature selection methods are utilized to select discriminative terms from high-
dimensional text data to improve text classification performance and reduce computational …

Measuring crack depth via normalized deformation profiles from digital image correlation based on optimum correlation

C Chen, X Qian, T Liu - Theoretical and Applied Fracture Mechanics, 2024 - Elsevier
This paper proposes a novel method to quantify the crack depth through the normalized
deformation profiles measured by digital image correlation (DIC). This study determines the …

Feature SELECTION on K-nearest neighbor algorithm using similarity measure

R Puspadini, H Mawengkang… - 2020 3rd International …, 2020 - ieeexplore.ieee.org
Data mining was the data processing technique to be obtained knowledge or important
pattern of data. One of the popular methods was the KNN (K-Nearest Neighbor) which was …

Application of metaheuristics for the feature selection problem

G Kalayci - 2019 - search.proquest.com
Feature selection aims to gain a minimal feature subset in a problem domain while
conserving the accuracy of the original data. Feature selection is a process for making more …

An effective two-stage feature selection method with parameters optimized by simulated annealing algorithm

Z Yang, J Ren - 2018 5th International Conference on …, 2018 - ieeexplore.ieee.org
With the increase of the dimension of the collected data, the research of feature selection
has gained more and more attention in recent years. As an essential preprocessing method …

[引用][C] TF-IDF Empowered Content-Based Recommendation System for Labor Complaints and Service Operations

MA Dini, DS Kim, JM Lee, T Jun - 한국통신학회학술대회논문집, 2023 - dbpia.co.kr
In the automotive industry, recommendation systems have gained prominence as vital tools
for addressing user preferences. This study introduces a tailored content-based …