scholarly journals An Comprehensive Survey on Applications of Precision Agriculture in the Context of Weed Classification, Leave Disease Detection, Yield Prediction and UAV Image Analysis

2021 ◽  
Author(s):  
Preethi C ◽  
Brintha NC ◽  
Yogesh CK
Keyword(s):  
Image Analysis ◽  
Precision Agriculture ◽  
The State ◽  
Disease Detection ◽  
Yield Prediction ◽  
Comprehensive Survey ◽  
Uav Images ◽  
Uav Image ◽  
Image Analysis Techniques ◽  
State Of Art

Advancement in technologies such as Machine vision, Machine Learning, Deep Learning algorithms enables them to extend its horizon in different applications including precision agriculture. The objective of this work is to study the various works pertaining to precision agriculture under four categories, weed classification, disease detection in leaves, yield prediction and image analysis techniques in UAV. In case of the weed classification, both classifying weeds from the crops and classifying the different types of weeds are analysed. In disease detection, only the diseases that occur in the leaves of different plants are considered and studied. It is continued with the state of art models that predicts yields of different crops. The last part of the work concentrates on analysing the images captured UAV in the context of precision agriculture. This work would pave a way for getting a deep insight about the state of art models related to the above specified applications of precision agriculture and the methods of analysing the UAV images.

scholarly journals VddNet: Vine Disease Detection Network Based on Multispectral Images and Depth Map

2020 ◽  
Vol 12 (20) ◽  
pp. 3305
Author(s):  
Mohamed Kerkech ◽  
Adel Hafiane ◽  
Raphael Canals
Keyword(s):  
Deep Learning ◽  
Precision Agriculture ◽  
Depth Map ◽  
Semantic Segmentation ◽  
Learning Technologies ◽  
Disease Detection ◽  
Registration Method ◽  
Multispectral Data ◽  
3D Processing ◽  
Uav Images

Vine pathologies generate several economic and environmental problems, causing serious difficulties for the viticultural activity. The early detection of vine disease can significantly improve the control of vine diseases and avoid spread of virus or fungi. Currently, remote sensing and artificial intelligence technologies are emerging in the field of precision agriculture. They offer interesting potential for crop disease management. However, despite the advances in these technologies, particularly deep learning technologies, many problems still present considerable challenges, such as semantic segmentation of images for disease mapping. In this paper, we present a new deep learning architecture called Vine Disease Detection Network (VddNet). It is based on three parallel auto-encoders integrating different information (i.e., visible, infrared and depth). Then, the decoder reconstructs and retrieves the features, and assigns a class to each output pixel. An orthophotos registration method is also proposed to align the three types of images and enable the processing by VddNet. The proposed architecture is assessed by comparing it with the most known architectures: SegNet, U-Net, DeepLabv3+ and PSPNet. The deep learning architectures were trained on multispectral data from an unmanned aerial vehicle (UAV) and depth map information extracted from 3D processing. The results of the proposed architecture show that the VddNet architecture achieves higher scores than the baseline methods. Moreover, this study demonstrates that the proposed method has many advantages compared to methods that directly use the UAV images.

Opponent Center-Surround Contrast: Colour to Grey Conversion

2020 ◽  
Vol 2020 (1) ◽  
pp. 105-108
Author(s):  
Ali Alsam
Keyword(s):  
Evolutionary Algorithms ◽  
Three Dimensional ◽  
The State ◽  
Colour Space ◽  
Vision Science ◽  
State Of Art ◽  
Over Time

Vision is the science that informs us about the biological and evolutionary algorithms that our eyes, opticnerves and brains have chosen over time to see. This article is an attempt to solve the problem of colour to grey conversion, by borrowing ideas from vision science. We introduce an algorithm that measures contrast along the opponent colour directions and use the results to combine a three dimensional colour space into a grey. The results indicate that the proposed algorithm competes with the state of art algorithms.

Kidney transplantation in identical twins: the state of art and a case report

2019 ◽  
Vol 21 (4) ◽  
pp. 458-465
Author(s):  
A.I. Sushkov ◽  
◽  
T.A. Astrelina ◽  
E.V. Shestero ◽  
V.A. Nikitina ◽  
...  
Keyword(s):  
Kidney Transplantation ◽  
Case Report ◽  
The State ◽  
Identical Twins ◽  
State Of Art

A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

2019 ◽  
Author(s):  
Mukhil Azhagan M. S ◽  
Dhwani Mehta ◽  
Hangwei Lu ◽  
Sudarshan Agrawal ◽  
Mark Tehranipoor ◽  
...  
Keyword(s):  
Image Analysis ◽  
Visual Inspection ◽  
Automated System ◽  
Imaging Modalities ◽  
Future Research ◽  
Analysis Techniques ◽  
Bill Of Materials ◽  
Pros And Cons ◽  
Index Terms ◽  
Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals A Review of Size Engineering-Enabled Electrocatalysts for Li–S Chemistry

2021 ◽  
Author(s):  
Xi Zhang ◽  
Yaping Zhang ◽  
xijun wei ◽  
Chaohui Wei ◽  
Yingze Song
Keyword(s):  
Energy Density ◽  
High Energy ◽  
The State ◽  
High Energy Density ◽  
State Of Art

Li–S batteries (LBSs) have received extensive attention owing to their remarkable theoretical capacity (1672 mA h g–1) and high energy density (2600 Wh kg–1), far beyond the state of art...

scholarly journals A Systematic Review of Recommender Systems and Their Applications in Cybersecurity

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5248
Author(s):  
Aleksandra Pawlicka ◽  
Marek Pawlicki ◽  
Rafał Kozik ◽  
Ryszard S. Choraś
Keyword(s):  
Systematic Review ◽  
Recommender Systems ◽  
Recommender System ◽  
State Of The Art ◽  
The State ◽  
Advantages And Disadvantages ◽  
Comprehensive Survey ◽  
Security Concerns ◽  
Valuable Role

This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

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