counting the population of insect pests is a key task for planning a successful integrated pest management program. most image processing and machine vision techniques in the literature are very site-specific and cannot be easily re-usable because their performances are highly related to their ground truth data. in this article a new unsupervised image processing method is proposed which is gen...

abstract- the evaluation of leaf area and leaf nutritional value is important for crop growth modeling and estimations of its performance. the purpose of this study was to use image processing techniques to develop an economical method to ease the assessment of nutrient status and leaf area (la) of plants and to compare the outcomes of this method with linear models. leaf area and leaf chloroph...

detecting faces in cluttered backgrounds and real world has remained as an unsolved problem yet. in this paper, by using composition of some kind of independent features and one of the most common appearance based approaches, and multilayered perceptron (mlp) neural networks, not only some questions have been answered, but also the designed system achieved better performance rather than the pre...

Blind source separation (BSS) refers to a wide class of methods in signal and image processing, which extract the underlying sources from a set of mixtures without almost any prior knowledge about the sources nor about the mixing process. In biomedical applications, BSS is used for the analysis of electroencephalogram (EEG), magenetoencephalogram (MEG) and electrocardiogram (ECG) signals and fu...

A key step in medical image-based diagnosis is image segmentation. common use case for segmentation the identification of single structures an elliptical shape. Most organs like heart and kidneys fall into this category, as well skin lesions, polyps, other types abnormalities. Neural networks have dramatically improved results, but still require large amounts training data long times to converg...

The current methods of turfgrass evaluations are often based on human-based assessment methods. However, eliminating subjective errors from such evaluations is often impossible. This research compared the accuracy of human-based and digital image processing-based methods for quality assessment of turfgrasses. Four turfgrass plots were evaluated using the two mentioned methods. In the human-base...

Compression is a standard procedure for making convolutional neural networks (CNNs) adhere to some specific computing resource constraints. However, searching compressed architecture typically involves series of time-consuming training/validation experiments determine good compromise between network size and performance accuracy. To address this, we propose an image complexity-guided compressio...

Introduction: In spite of all the researches on medical imaging, this field is still hot. It is the third major area of research, conducted in the world. Unfortunately, there is no statistical evaluation available of the student theses in Iran. It does not seem like a policy is going to be established to address this issue. Providing a statistical insight to activities done in ...

The current methods of turfgrass evaluations are often based on human-based assessment methods. However, eliminating subjective errors from such evaluations is often impossible. This research compared the accuracy of human-based and digital image processing-based methods for quality assessment of turfgrasses. Four turfgrass plots were evaluated using the two mentioned methods. In the human-base...