![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Advancing automatic plant classification system in Saudi Arabia: introducing a novel dataset and ensemble deep learning approach
Automated plant detection plays a pivotal role in various domains, including agriculture, environmental monitoring, and biodiversity conservation. In this paper presents a novel deep learning model specificall...
-
Chapter and Conference Paper
A Table Extraction Solution for Financial Spreading
Financial spreading is a necessary exercise for financial institutions to break up the analysis of financial data in making decisions like investment advisories, credit appraisals, and more. It refers to the c...
-
Chapter and Conference Paper
SSFuzzyART: A Semi-Supervised Fuzzy ART Through Seeding Initialization
Semi-supervised clustering is a machine learning technique that was introduced to boost clustering performance when labelled data is available. Indeed, labelled data are usually available in real use cases, an...
-
Article
Evidential positive opinion influence measures for viral marketing
The viral marketing is a relatively new form of marketing that exploits social networks to promote a brand, a product, etc. The idea behind it is to find a set of influencers on the network that can trigger a ...
-
Chapter and Conference Paper
An Evidential k-nearest Neighbors Combination Rule for Tree Species Recognition
The task of tree species recognition is to recognize the tree species using photos of their leaves and barks. In this paper, we propose an evidential k-nearest neighbors (k-NN) combination rule. The proposed rule...
-
Chapter and Conference Paper
Evidential Independence Maximization on Twitter Network
Detecting independent users in online social networks is an interesting research issue. In fact, independent users cannot generally be influenced, they are independent in their choices and decisions. Independe...
-
Chapter and Conference Paper
A Reliability-Based Approach for Influence Maximization Using the Evidence Theory
The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing camp...
-
Chapter and Conference Paper
Dynamic Time War** Distance for Message Propagation Classification in Twitter
Social messages classification is a research domain that has attracted the attention of many researchers in these last years. Indeed, the social message is different from ordinary text because it has some spec...
-
Chapter and Conference Paper
Classification of Message Spreading in a Heterogeneous Social Network
Nowadays, social networks such as Twitter, Facebook and LinkedIn become increasingly popular. In fact, they introduced new habits, new ways of communication and they collect every day several information that ...
-
Chapter and Conference Paper
Second-Order Belief Hidden Markov Models
Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model. First-order probabilistic HMMs were adapt...