Blurred trace infrared image segmentation based on template approach and immune factor

Fractional-order calculus-based flower pollination algorithm with local search for global optimization and image segmentation

“…To investigate the efficiency of the FO-FPA approach, we applied it as a multilevel threshold (MLT) image segmentation method as a real-world application [44]. Since the image segmentation is considered a prepossessing step in different applications for example, medical image [45], remote sensing [46], infrared images [47,48] and others [49,50,51,51,52]. The main aim of the MLT image segmentation is to allocate the threshold values that divide the images into number of groups according to some criteria [53].…”

Improving the generalization performance of deep networks by dual pattern learning with adversarial adaptation

“…Convolutional neural networks (CNNs) have become a dominant approach for various machine learning applications such as computer vision [1,2,3,4,5], natural language processing [6,7,8], and reinforcement learning [9,10]. Integrating feature learning and classifiers in an end-to-end manner, deep neural networks can learn features automatically from training data without human involvement during training.…”

An Associate Rules Mining Algorithm Based on Artificial Immune Network for SAR Image Segmentation

“…Recently, Fu et al proposed a coordinated immune network template algorithm [6], and it added a coordination mechanism between innate immunity and adaptive immunity in order to extract targets from blurred infrared images. More recently, an image segmentation method for blurred trace infrared images was proposed in [7], which was considered the function of immune factors for blurred infrared image segmentation. The simulation results show that this method can improve the target segmentation rate and reduce the segmentation error rate.…”