Systematic review of deep learning techniques in plant disease detection
Automatic identification of diseases through hyperspectral images is a very critical and
primary challenge for sustainable farming and gained the attention of researchers during the …
primary challenge for sustainable farming and gained the attention of researchers during the …
A novel hybrid severity prediction model for blast paddy disease using machine learning
Hypothesis: Due to the increase in the losses in paddy yield as a result of various paddy
diseases, researchers are working tirelessly for a technological solution to assist farmers in …
diseases, researchers are working tirelessly for a technological solution to assist farmers in …
An efficient malware detection approach with feature weighting based on Harris Hawks optimization
This paper introduces and tests a novel machine learning approach to detect Android
malware. The proposed approach is composed of Support Vector Machine (SVM) classifier …
malware. The proposed approach is composed of Support Vector Machine (SVM) classifier …
An optimal pruning algorithm of classifier ensembles: dynamic programming approach
In recent years, classifier ensemble techniques have drawn the attention of many
researchers in the machine learning research community. The ultimate goal of these …
researchers in the machine learning research community. The ultimate goal of these …
Analysis of machine learning classifiers for early detection of DDoS attacks on IoT devices
Distributed denial-of-service attacks are still difficult to handle as per current scenarios. The
attack aim is a menace to network security and exhausting the target networks with …
attack aim is a menace to network security and exhausting the target networks with …
Supervised link prediction using structured‐based feature extraction in social network
Social network analysis (SNA) has attracted a lot of attention in several domains in the past
decades. It can be of 2‐folds: one is content‐based, and another one is structured‐based …
decades. It can be of 2‐folds: one is content‐based, and another one is structured‐based …
[PDF][PDF] A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System.
O Almomani - Computers, Materials & Continua, 2021 - academia.edu
Network Intrusion Detection System (IDS) aims to maintain computer network security by
detecting several forms of attacks and unauthorized uses of applications which often can not …
detecting several forms of attacks and unauthorized uses of applications which often can not …
Constructing multi-layer classifier ensembles using the Choquet integral based on overlap and quasi-overlap functions
Ensembles of classifiers have been receiving much attention lately, they consist of a
collection of classifiers that process the same information and their output is combined in …
collection of classifiers that process the same information and their output is combined in …
A new hybrid ensemble model with voting-based outlier detection and balanced sampling for credit scoring
W Zhang, D Yang, S Zhang - Expert Systems with Applications, 2021 - Elsevier
The credit scoring system has been revolutionized with the development of the financial
system and has received increasing attention from the academia and industry. Artificial …
system and has received increasing attention from the academia and industry. Artificial …
Bipolar fully recurrent deep structured neural learning based attack detection for securing industrial sensor networks
JA Alzubi - Transactions on Emerging Telecommunications …, 2021 - Wiley Online Library
Attack detection is a significant problem to be resolved to attain security in industrial sensor
network. Few research works have been designed for performing attack discovery process …
network. Few research works have been designed for performing attack discovery process …