Detection and Separation of Smoke From Single Image Frames.

This paper proposes novel methods for detecting and separating smoke from a single image frame. Specifically, an image formation model is derived based on the atmospheric scattering models. The separation of a frame into quasi-smoke and quasi-background components is formulated as convex optimization that solves a sparse representation problem using dual dictionaries for the smoke and background components, respectively.

Automatic non-proliferative diabetic retinopathy screening system based on color fundus image.

Background: Non-proliferative diabetic retinopathy is the early stage of diabetic retinopathy. Automatic detection of non-proliferative diabetic retinopathy is significant for clinical diagnosis, early screening and course progression of patients.

Methods: This paper introduces the design and implementation of an automatic system for screening non-proliferative diabetic retinopathy based on color fundus images.

Detection of ground parrot vocalisation: A multiple instance learning approach.

Ground parrot vocalisation can be considered as an audio event. Test-based diverse density multiple instance learning (TB-DD-MIL) is proposed for detecting this event in audio files recorded in the field. The proposed method is motivated by the advantages of multiple instance learning from incomplete training data.