We describe a novel framework for the joint processing of color and shape information in natural images. A hierarchical non-linear spatio-chromatic operator yields spatial and chromatic opponent channels, which mimics processing in the primate visual cortex. We extend two popular object recognition systems (i.e., the Hmax hierarchical model of visual processing and a sift-based bag-of-words app...

Oxygen binds to hemoglobin cooperatively, and a correct description of this binding is relevant not only for understanding the mechanisms involved molecular processes but also clinical purposes. Hill’s equation, derived over hundred years ago, still simplest most efficient way perform description. However, in terms accuracy, it inferior Adair´s which contains more parameters. We proposed use mo...

The retention-releasing patterns of the double-grid grating sieve placed on deck purse seiners were revealed for four case species (Sardina pilchardus, Sardinella aurita, Engraulis encrasicolus and Boops boops) using a simulated data predicted from total length (TL) – maximum height (Hmax) TL width (Wmax) regressions. To calculate these relationships, samples collected during commercial seine o...

Understanding how functional traits and diversity modulate plant interactions within forests is becoming a widespread research goal in ecology. We applied neighbourhood analysis to Mediterranean biodiversity manipulation experiment (IDENT-Macomer) assess the importance of predicting tree diameter increments (DI) mixed forest. used weigh competition index (NCI) dispersion (FDis), which metric. f...

Abstract Information about the absolute stress state in upper crust plays a crucial role planning and execution of, e.g., directional drilling, stimulation exploitation of geothermal hydrocarbon reservoirs. Since many these applications are related to sediments, we present refined geomechanical–numerical model for Germany with focus on sedimentary basins, able predict complete 3D tensor. The la...

Humans use visual context to improve object recognition. Yet, many machine vision algorithms still focus on local object features, discarding surrounding features as unwanted clutter. Here we study the impact of learning contextual cues while training an object classifier. In a new image database with 10 object categories and 28,800 images, objects were presented in contextual or uniform backgr...

In this paper we study the role of movement strategies during learning in object recognition models. We show that a simple model, the RBF, can outperform a more complex hierarchical model, the HMAX, when rotation and scale invariance are provided by the training phase. Moreover, we assess the exploitation of temporal information by the RBF using optic flow. The results show that the RBF model c...

Object detection and localization is a challenging task. Among several approaches, more recently hierarchical methods of feature-based object recognition have been developed and demonstrated high-end performance measures. Inspired by the knowledge about the architecture and function of the primate visual system, the computational HMAX model has been proposed. At the same time robust visual obje...