4 citations · 4 across the 4 of their papers we have counts for
4 papers
Optimizing method for Neural Network based on Genetic Random Weight Change Learning Algorithm
Mohammad Ibrahim Sarker, Zubaer Ibna Mannan, Hyongsuk Kim
Random weight change (RWC) algorithm is extremely component and robust for the hardware implementation of neural networks. RWC and Genetic algorithm (GA) are well known methodologi…
Corn leaf detection using Region based convolutional neural network
Mohammad Ibrahim Sarker, Heechan Yang, Hyongsuk Kim
The field of machine learning has become an increasingly budding area of research as more efficient methods are needed in the quest to handle more complex image detection challenge…
Genetic Random Weight Change Algorithm for the Learning of Multilayer Neural Networks
Mohammad Ibraim Sarker, Yali Nie, Hong Yongki +1
A new method to improve the performance of Random weight change (RWC) algorithm based on a simple genetic algorithm, namely, Genetic random weight change (GRWC) is proposed. It is…
Farm land weed detection with region-based deep convolutional neural networks
Mohammad Ibrahim Sarker, Hyongsuk Kim
Machine learning has become a major field of research in order to handle more and more complex image detection problems. Among the existing state-of-the-art CNN models, in this pap…