A large body of research in supervised learning deals with the analysis of single-label data,
where training examples are associated with a single label λ from a set of disjoint labels L …

Nowadays, more and more images are available. However, to find a required image for an
ordinary user is a challenging task. Large amount of researches on image retrieval have …

Multiple instance learning (MIL) is a form of weakly supervised learning where training
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …

The capability of recognizing pedestrian attributes, such as gender and clothing style, at far
distance, is of practical interest in far-view surveillance scenarios where face and body close …

Partial multi-label learning (PML) deals with problems where each instance is assigned with
a candidate label set, which contains multiple relevant labels and some noisy labels. Recent …

In general image recognition problems, discriminative information often lies in local image
patches. For example, most human identity information exists in the image patches …

Labeling a histopathology image as having cancerous regions or not is a critical task in
cancer diagnosis; it is also clinically important to segment the cancer tissues and cluster …

Recently, image categorization has been an active research topic due to the urgent need to
retrieve and browse digital images via semantic keywords. This paper formulates image …

Try this experiment. Turn on your television with the sound off. Now change channels with
your eyes closed. At each new channel, blink quickly. As the picture appears, you will …

Although field-collected recordings typically contain multiple simultaneously vocalizing birds
of different species, acoustic species classification in this setting has received little study so …