The purpose of this study was to identify the kinematic and kinetic strategies used by patients with unilateral triple arthrodesis or subtalar fusion during level walking, stair ascent, stair descent and to determine the influence of these different conditions on kinematics and kinetics. Nine subjects with unilateral triple or subtalar fusion and five normal control subjects were recruited for ...

Needle segmentation is a fundamental step for needle reconstruction and image-guided surgery. Although there has been success stories in needle segmentation for non-microsurgeries, the methods cannot be directly extended to ophthalmic surgery due to the challenges bounded to required spatial resolution. As the ophthalmic surgery is performed by finer and smaller surgical instruments in micro-st...

The task of estimating the spatial layout of cluttered indoor scenes from a single RGB image is addressed in this work. Existing solutions to this problems largely rely on hand-craft features and vanishing lines, and they often fail in highly cluttered indoor rooms. The proposed coarse-to-fine indoor layout estimation (CFILE) method consists of two stages: 1) coarse layout estimation; and 2) fi...

Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs) have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satisfactory. Based on the analysis of visual mechanism, we conclude that DCNNs in a bottom-up manner are not enough, because semantic image segmentatio...

OBJECTIVES We investigated the possible association of rheumatoid arthritis (RA) with single nucleotide polymorphisms (SNP) within the ficolin (FCN) genes. Two SNPs in the FCN1 gene, four SNPs in the FCN2 gene and one SNP in the FCN3 gene were studied. METHODS The SNPs within the FCN genes were detected by an experimental INNO-LiPA methodology (Innogenetics, Belgium) in a population consistin...

With recent innovations in dense image captioning, it is now possible to describe every object of the scene with a caption while objects are determined by bounding boxes. However, interpretation of such an output is not trivial due to the existence of many overlapping bounding boxes. Furthermore, in current captioning frameworks, the user is not able to involve personal preferences to exclude o...

Crop diseases are responsible for the major production reduction and economic losses in agricultural industry worldwide. Monitoring for health status of crops is critical to control the spread of diseases and implement effective management. This paper presents an in-field automatic wheat disease diagnosis system based on a weakly supervised deep learning framework, i.e. deep multiple instance l...

In this paper we review the evolution of deep architectures for semantic segmentation. The first successful model was fully convolutional network (FCN) published in CVPR 2015. Since then, subject has become very popular and many methods have been published, mainly proposing improvements FCN. We describe detail Pyramid Scene Parsing Network (PSPnet) DeepLabV3, addition to FCN, which provide a mu...

This paper presents a novel method to involve both spatial and temporal features for semantic segmentation of street scenes. Current work on convolutional neural networks (CNNs) has shown that CNNs provide advanced spatial features supporting a very good performance of solutions for the semantic segmentation task. We investigate how involving temporal features also has a good effect on segmenti...