Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this paper, we propose a novel bio-inspired network, named the MirrorNet, that leverages both instance segmentation and attack stream camouflaged object segmentation. Differently from existing networks segmentation, our proposed network possesses two streams: main corresponding with...

For extracting the equivalent circuit parameters of solar photovoltaic (PV) panels, a unique bio-inspired swarm intelligence optimisation algorithm (OA) called dandelion (DOA) is proposed in this study. The suggested approach has been used to analyse well-known single-diode (SD) and double-diode (DD) PV models for several module types, including monocrystalline SF430M, polycrystalline SG350P, t...

In this paper, a new Bio-inspired algorithm, namely kudu herd algorithm (KHA) is proposed for solving reactive power dispatch problem. A population of candidate solution approach as a herd of kudus carries out a succession of jumps through the search space in order to find the most excellent solution. The logic of this algorithm is quite different from that of most population based algorithms, ...

Humans use visual context to improve object recognition. Yet, many machine vision algorithms still focus on local object features, discarding surrounding features as unwanted clutter. Here we study the impact of learning contextual cues while training an object classifier. In a new image database with 10 object categories and 28,800 images, objects were presented in contextual or uniform backgr...