Comprehensive review of artificial neural network applications to pattern recognition
The era of artificial neural network (ANN) began with a simplified application in many fields
and remarkable success in pattern recognition (PR) even in manufacturing industries …
and remarkable success in pattern recognition (PR) even in manufacturing industries …
Applications of machine learning in alloy catalysts: rational selection and future development of descriptors
Z Yang, W Gao - Advanced Science, 2022 - Wiley Online Library
At present, alloys have broad application prospects in heterogeneous catalysis, due to their
various catalytic active sites produced by their vast element combinations and complex …
various catalytic active sites produced by their vast element combinations and complex …
A new class of Hopfield neural network with double memristive synapses and its DSP implementation
T Ma, J Mou, H Yan, Y Cao - The European Physical Journal Plus, 2022 - Springer
The nonlinear characteristics are studied in a new 4D Hopfield neural network model with
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …
two nonlinear synaptic weights in this paper. The synaptic function is modeled by …
Computer-aided detection of breast cancer on the Wisconsin dataset: An artificial neural networks approach
The early detection of breast cancer (BC) has a significant impact on reducing the disease's
mortality rate. As an effective cost-and time-saving tool, computer-aided diagnosis (CAD) …
mortality rate. As an effective cost-and time-saving tool, computer-aided diagnosis (CAD) …
Detection of online phishing email using dynamic evolving neural network based on reinforcement learning
Despite state-of-the-art solutions to detect phishing attacks, there is still a lack of accuracy for
the detection systems in the online mode which is leading to loopholes in web-based …
the detection systems in the online mode which is leading to loopholes in web-based …
The orb-weaving spider algorithm for training of recurrent neural networks
AS Mikhalev, VS Tynchenko, VA Nelyub, NM Lugovaya… - Symmetry, 2022 - mdpi.com
The quality of operation of neural networks in solving application problems is determined by
the success of the stage of their training. The task of learning neural networks is a complex …
the success of the stage of their training. The task of learning neural networks is a complex …
Leaf disease detection and grading using computer vision technology & fuzzy logic
In Agriculture, leaf diseases have grown to be a dilemma as it can cause significant
diminution in both quality and quantity of agricultural yields. Thus, automated recognition of …
diminution in both quality and quantity of agricultural yields. Thus, automated recognition of …
Optimization of modular granular neural networks using a firefly algorithm for human recognition
In this paper a new optimization method for modular neural network (MNN) design using
granular computing and a firefly algorithm is proposed. This method is tested with human …
granular computing and a firefly algorithm is proposed. This method is tested with human …
Optical camera communications: Principles, modulations, potential and challenges
Optical wireless communications (OWC) are emerging as cost-effective and practical
solutions to the congested radio frequency-based wireless technologies. As part of OWC …
solutions to the congested radio frequency-based wireless technologies. As part of OWC …
Mammograms classification using gray-level co-occurrence matrix and radial basis function neural network
M Pratiwi, J Harefa, S Nanda - Procedia Computer Science, 2015 - Elsevier
Abstract Computer Aided Diagnosis (CAD) is used to assist radiologist in classifying various
type of breast cancers. It already proved its success not only in reducing human error in …
type of breast cancers. It already proved its success not only in reducing human error in …