Accurate and real-time forecasting of the price oil plays an important role in world economy. Research interest this type time series has increased considerably recent decades, since, due to characteristics series, it was a complicated task with inaccurate results. Concretely, deep learning models such as Convolutional Neural Networks (CNNs) Recurrent (RNNs) have appeared field promising results compared traditional approaches. To improve performance existing networks forecasting, work two...

An important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two groups can be appropriately controlled by specific herbicides. In fact, efficiency higher if selective treatment performed for each type of infestation instead using a broadcast herbicide on whole surface. This work proposes strategy where are characterised set shape descriptors (the seven Hu moments six geometric descriptors). Weeds appear outdoor...

The dynamics of a skid-steering robot present intrinsic non-linearities that make the design and implementation controller very complex task, time-consuming, difficult to implement into an embedded system with limited resources. This paper presents simplified first order digital model approximation optimal observer-based control approach for tracking lateral position such robots. In verify validity this proposal, 3D real-time interactive simulations real validations agricultural were...

In recent years, proximal sensing data has increasingly been used to optimize forest inventories. this paper we present a inventory methodology based on stereoscopic hemispherical images. An automated pixel-based approach and user-guided “region growing” have developed for image matching. To estimate the basal area, number of trees mean diameter, sampling probability is determined each tree. The accuracy precision estimates derived from images was analyzed set National Forest Inventory...

We present a novel strategy for computing disparity maps from hemispherical stereo images obtained with fish-eye lenses in forest environments. At first segmentation stage, the method identifies textures of interest to be either matched or discarded. This is achieved by applying pattern recognition based on combination two classifiers: Fuzzy Clustering and Bayesian. second stereovision matching process performed application four constraints: epipolar, similarity, uniqueness smoothness. The...

This paper describes a novel feature-based stereovision matching process based on pair of omnidirectional images in forest stands acquired with sensor equipped fish-eye lenses. The stereo analysis problem consists the following steps: image acquisition, camera modelling, feature extraction, and depth determination. Once depths significant points trees are obtained, growing stock volume can be estimated by considering geometrical which is final goal. key steps extraction matching. devoted...

This paper describes a new automatic image segmentation strategy for segmenting green plants. The final goal is its application in Precision Agriculture. to identify several classes of greenness coming from the We exploit performance existing approaches so that conveniently combined allow us design approach based on non methods. First we apply well known index-based accentuates spectral band remainder, giving gray image. From resulting well-known thresholding Otsu's method obtaining binary...

This work presents a novel strategy to decipher fragments of Egyptian cartouches identifying the hieroglyphs which they are composed. A cartouche is drawing, usually inside an oval, that encloses group representing name monarch. Aiming identify these drawings, proposed method based on several techniques frequently used in computer vision and consists three main stages: first, picture taken as input its contour localized. In second stage, each hieroglyph individually extracted identified....

In peer assessment, students assess a task done by their peers, provide feedback and usually grade. The extent to which these grades can be used formally grade the is unclear, with doubts often arising regarding validity. instructor could supervise assessments, but would not then benefit from workload reduction, one of most appealing features assessment for instructors. Our proposal uses probabilistic model estimate each test, accounting degree precision bias grading peers. that assign test...

A new automatic hybrid classifier for natural images by combining two base classifiers through the fuzzy cognitive maps (FCMs) approach is presented in this study. The used are clustering (FC) and parametric Bayesian (BP) method. During training phase, different partitions established until a valid partition found. Partitioning validation processes based on measurements. From partition, parameters of both estimated. classification FC provides each pixel supports (membership degrees) that...

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds data sensed during flights. classification natural spectral signatures in images is one potential application. actual tendency oriented towards combination simple classifiers. In this paper we propose a combined strategy based Deterministic Simulated Annealing (DSA) framework....

This paper describes a device, based on stereovision, which is designed for forest inventories purposes. It captures pairs of omni-directional stereoscopic images through fish-eye lens, from different tri-dimensional measures can be obtained by applying stereovision process, including image acquisition, feature and attribute extraction, matching depth determination. explains summarizes two specific methods solving the problem, as key step in stereovision. They are pixel-based region-based,...