%0 Journal Article %T Individual Minke Whale Recognition Using Deep Learning Convolutional Neural Networks %A Dmitry A. Konovalov %A Suzanne Hillcoat %A Genevieve Williams %A R. Alastair Birtles %A Naomi Gardiner %A Matthew I. Curnock %J Journal of Geoscience and Environment Protection %P 25-36 %@ 2327-4344 %D 2018 %I Scientific Research Publishing %R 10.4236/gep.2018.65003 %X
The only known predictable aggregation of dwarf minke whales (Balaenoptera acutorostrata subsp.) occurs in the Australian offshore waters of the northern Great Barrier Reef in May-August each year. The identification of individual whales is required for research on the whales¡¯ population characteristics and for monitoring the potential impacts of tourism activities, including commercial swims with the whales. At present, it is not cost-effective for researchers to manually process and analyze the tens of thousands of underwater images collated after each observation/tourist season, and a large data base of historical non-identified imagery exists. This study reports the first proof of concept for recognizing individual dwarf minke whales using the Deep Learning Convolutional Neural Networks (CNN).The ¡°off-the-shelf¡± Image net-trained VGG16 CNN was used as the feature-encoder of the perpixel sematic segmentation Automatic Minke Whale Recognizer (AMWR). The most frequently photographed whale in a sample of 76 individual whales (MW1020) was identified in 179 images out of the total 1320 images provid-ed. Training and image augmentation procedures were developed to compen-sate for the small number of available images. The trained AMWR achieved 93% prediction accuracy on the testing subset of 36 positive/MW1020 and 228 negative/not-MW1020 images, where each negative image contained at least one of the other 75 whales. Furthermore on the test subset, AMWR achieved 74% precision, 80% recall, and 4% false-positive rate, making the presented approach comparable or better to other state-of-the-art individual animal recognition results.
%K Dwarf Minke Whales %K Photo-Identification %K Population Biology %K Convolutional Neural Networks %K Deep Learning %K Image Recognition %U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=84616