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An Optical Character Recognition (OCR) approach for printed Arabic script is presented in this paper, Which is one of the most popular scripts in the world. Development of an OCR system. For Arabic script it is difficult...

Chip-scale integrated optical signal processors promise to support a multitude of signal processing functions with bandwidths beyond the limit of microelectronics. Previous research has made great contributions in terms ...

The aim of this study is the early detection of developing insulation defects in high-voltage oil-filled bushings based on the analysis of the temporal behavior of diagnostic indicators rather than only their comparison ...

One of the most evident costs in cow farming is the identification of the animals. Classic identification processes are labour-intensive, prone to human errors and invasive for the animal. An automated alternative is an ...

Photonic computing and neuromorphic computing are attracting tremendous interests in breaking the memory wall of traditional von Neumann architecture. Photonic memristors equipped with light sensing, data storage, and in...

Abstract Satellite Image Classification is a process in remote sensing that aims at classifying pixels of satellite imagery into usable information of land use and land cover. This information is not only limited to seve...

The increasing lack and limitations of key cereals such as rice and wheat, aggravated by climate change, growing population, and declining agricultural sustainability, pose significant threats to global food and nutritio...

Abstract Background Enhancing nitrogen use efficiency (NUE) is essential for sustainable agriculture. Stress response pathways play a significant role in regulating NUE across various growth stages and organs. Therefore,...

Abstract Researches and techniques of pattern recognition aim at finding and developing techniques for recognizing certain patterns or structures in the digital signals. A signal can represent a sound segment or a verbal...

Abstract Background Machine learning methods are widely used to detect behavioural data patterns. Although these new mathematical methods are useful tools, the interpretation of the results are often ambivalent unless ...

UAV (Unmanned Airborne Vehicle) high resolution digital image acquisition systems based on small format cameras provide a versatile alternative to the solution of environmental monitoring and remote sensing problems. Thr...

Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models (GMMs) to determine how well each state of each HMM fits a frame or a sh...

Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrar...

This paper presents a robust eye detection algorithm for gray intensity images. The idea of our method is to combine the respective advantages of two existing techniques, feature based method and template based method, a...

Boundary extraction is an important procedure associated with recognition and interpretation tasks in digital image processing and computer vision. Most of the segmentation techniques are based on the detection of the lo...

The authors introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions. These waveforms are chosen in order...

The discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. In this paper, we take one step forward by investigating the construc...

An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are pre...

We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVR...

This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to be ...

This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This work is distinguished by three key contributio...

In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinatio...

In the first part of this paper, a regular recurrent neural network (RNN) is extended to a bidirectional recurrent neural network (BRNN). The BRNN can be trained without the limitation of using input information just up ...

Segmentation is often a critical step in image analysis. Microscope image components show great variability of shapes, sizes, intensities and textures. An inaccurate segmentation conditions the ulterior quantification a...