Automatic Hierarchical Classification of Kelps Using Deep Residual Features.

Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes for experts to identify organisms found in these images. With this limitation in mind, a large effort has been made globally to introduce automation and machine learning algorithms to accelerate both classification and assessment of marine benthic biota. One major issue lies with organisms that move with swell and currents, such as kelps. This paper presents an automatic hierarchical classification method local binary classification as opposed to the conventional flat classification to classify kelps in images collected by autonomous underwater vehicles. The proposed kelp classification approach exploits learned feature representations extracted from deep residual networks. We show that these generic features outperform the traditional off-the-shelf CNN features and the conventional hand-crafted features. Experiments also demonstrate that the hierarchical classification method outperforms the traditional parallel multi-class classifications by a significant margin (90.0% vs. 57.6% and 77.2% vs. 59.0%) on Benthoz15 and Rottnest datasets respectively. Furthermore, we compare different hierarchical classification approaches and experimentally show that the sibling hierarchical training approach outperforms the inclusive hierarchical approach by a significant margin. We also report an application of our proposed method to study the change in kelp cover over time for annually repeated AUV surveys.

Responses of four Indo-West Pacific seagrass species to shading.

Seagrasses of the Great Barrier Reef predominantly occur in coastal regions where terrestrial inputs modify water quality and photosynthetic light is highly variable. Responses to shading were tested for Cymodocea serrulata, Halodule uninervis, Thalassia hemprichii and Zostera muelleri. In aquaria, four light treatments - high (66% surface light), moderate (31%), low (14%) and very low light (1%) treatments - were applied for 102d. Stress responses in the low and very low light treatments occurred in the following sequence: metabolic and physiological changes (reduced growth, increased pigment concentrations and photosynthetic efficiency); shedding (leaf loss, shoot loss) and production of new, altered tissue (leaves with reduced length, width and thickness). Complete shoot loss was projected after 76 (Z. muelleri) to 130d (T. hemprichii). Responses were slower in the low than in the very low treatment, therefore, efforts to minimize water quality degradation will be rewarded with delayed impacts to seagrasses.