In this paper we propose a general framework for videobased object segmentation using a new spatio-temporal Markov Random Field (MRF) model. Video-based object segmentation has the potential to improve the performance of static image segmentation by fusing information over the temporal scale. Built upon a spatio-temporal MRF model, our method offers three advantages in a unified framework. Firs...

breast lesion segmentation in mr images is one of the most important parts of clinical diagnostic tools. pixel classification methods have been frequently used in image segmentation with two supervised and unsupervised approaches up to now. supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to be obtained. on t...

In this work, we propose a panoptic segmentation model that integrates bottom-up and top-down methods. Our framework is designed to guarantee both the performance inference speed. We also focus on improving quality of semantic instance masks. The proposed auxiliary task with silhouette-based enhanced features can help improve prediction mask contours. Additionally, introduce new score intending...

Selective visual attention to objects and locations depends both on deliberate behavioral goals that regulate even early visual representations (goal-directed influences) and on autonomous neural responses to sensory input (stimulus-driven influences). In this chapter, I argue that deliberate goal-directed attentional strategies are always constrained by involuntary, ”hard-wired computations, a...

We consider the problem of clustering under the constraint that data points in the same cluster are connected according to a pre-existed graph. This constraint can be efficiently addressed by an agglomerative clustering approach, which we exploit to construct a new fully automatic segmentation algorithm for color photographs. For image segmentation, if the pixel grid with eight neighbor connect...

This study deals with the familiarity effect (FE), which means that search performance is better when detecting an unfamiliar target in a familiar context compared to the detection performance of a familiar target in an unfamiliar context. In several experiments the spatial and temporal conditions were systematically varied to determine the ones which enable the appearance of the FE. Data were ...

Top-down and bottom up development policies have been generally sold as two irreconcilable ends of the development intervention spectrum. Top-down policies, solidly based in microand macroeconomic theories, but lacking the adequate flexibility and ‘place-awareness’ to respond to local complexity; bottom-up approaches much more responsive to diverse territorial needs, but devoid of a clear conce...

The study of discourse can be undertaken from different perspectives (e.g., linguistic, cognitive, or computational) with differing purposes in mind (e.g., to study language use or to analyze social practices). The aim of Discourse on the Move is to show that it is possible and profitable to join quantitative and qualitative analyses to study discourse structures. Whereas corpus-based quantitat...

Understanding the relative role of top-down and bottom-up guidance is crucial for models of visual search. Previous studies have addressed the role of top-down and bottom-up processes in search for a conjunction of features but with inconsistent results. Here, the author used an attentional capture method to address the role of top-down and bottom-up processes in conjunction search. The role of...