scholarly journals LeLePhid: An Image Dataset for Aphid Detection and Infestation Severity on Lemon Leaves

Data ◽  
2021 ◽  
Vol 6 (5) ◽  
pp. 51
Author(s):  
Jorge Parraga-Alava ◽  
Roberth Alcivar-Cevallos ◽  
Jéssica Morales Carrillo ◽  
Magdalena Castro ◽  
Shabely Avellán ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Plant Disease ◽  
Automatic Identification ◽  
Health State ◽  
Classification Problems ◽  
Affected Area ◽  
White Spots ◽  
The World ◽  
Image Dataset ◽  
Plant Sap

Aphids are small insects that feed on plant sap, and they belong to a superfamily called Aphoidea. They are among the major pests causing damage to citrus crops in most parts of the world. Precise and automatic identification of aphids is needed to understand citrus pest dynamics and management. This article presents a dataset that contains 665 healthy and unhealthy lemon leaf images. The latter are leaves with the presence of aphids, and visible white spots characterize them. Moreover, each image includes a set of annotations that identify the leaf, its health state, and the infestation severity according to the percentage of the affected area on it. Images were collected manually in real-world conditions in a lemon plant field in Junín, Manabí, Ecuador, during the winter, by using a smartphone camera. The dataset is called LeLePhid: lemon (Le) leaf (Le) image dataset for aphid (Phid) detection and infestation severity. The data can facilitate evaluating models for image segmentation, detection, and classification problems related to plant disease recognition.

scholarly journals Combining Leaf Shape and Texture for Costa Rican Plant Species

2016 ◽  
Author(s):  
Jose Carranza-Rojas ◽  
Erick Mata-Montero
Keyword(s):  
Costa Rica ◽  
Tree Species ◽  
Leaf Shape ◽  
Costa Rican ◽  
Automatic Identification ◽  
Leaf Margin ◽  
Best Value ◽  
Candidate Species ◽  
Image Dataset ◽  
Northeast Us

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of k , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research.

scholarly journals ResNet-Locust-BN Network-Based Automatic Identification of East Asian Migratory Locust Species and Instars from RGB Images

Insects ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 458
Author(s):  
Sijing Ye ◽  
Shuhan Lu ◽  
Xuesong Bai ◽  
Jinfeng Gu
Keyword(s):  
Structural Changes ◽  
East Asian ◽  
Activation Function ◽  
Learning Rate ◽  
Batch Size ◽  
Automatic Identification ◽  
Agricultural Pests ◽  
Migratory Locust ◽  
Initial Learning ◽  
The World

Locusts are agricultural pests found in many parts of the world. Developing efficient and accurate locust information acquisition techniques helps in understanding the relation between locust distribution density and structural changes in locust communities. It also helps in understanding the hydrothermal and vegetation growth conditions that affect locusts in their habitats in various parts of the world as well as in providing rapid and accurate warnings on locust plague outbreak. This study is a preliminary attempt to explore whether the batch normalization-based convolutional neural network (CNN) model can be applied used to perform automatic classification of East Asian migratory locust (AM locust), Oxya chinensis (rice locusts), and cotton locusts. In this paper, we present a way of applying the CNN technique to identify species and instars of locusts using the proposed ResNet-Locust-BN model. This model is based on the ResNet architecture and involves introduction of a BatchNorm function before each convolution layer to improve the network’s stability, convergence speed, and classification accuracy. Subsequently, locust image data collected in the field were used as input to train the model. By performing comparison experiments of the activation function, initial learning rate, and batch size, we selected ReLU as the preferred activation function. The initial learning rate and batch size were set to 0.1 and 32, respectively. Experiments performed to evaluate the accuracy of the proposed ResNet-Locust-BN model show that the model can effectively distinguish AM locust from rice locusts (93.60% accuracy) and cotton locusts (97.80% accuracy). The model also performed well in identifying the growth status information of AM locusts (third-instar (77.20% accuracy), fifth-instar (88.40% accuracy), and adult (93.80% accuracy)) with an overall accuracy of 90.16%. This is higher than the accuracy scores obtained by using other typical models: AlexNet (73.68%), GoogLeNet (69.12%), ResNet 18 (67.60%), ResNet 50 (80.84%), and VggNet (81.70%). Further, the model has good robustness and fast convergence rate.

scholarly journals Displacement in Nigeria: Scenes from the northeast

2017 ◽  
Vol 99 (904) ◽  
pp. 63-74
Keyword(s):  
Armed Conflict ◽  
Humanitarian Crisis ◽  
Affected Area ◽  
The World ◽  
Human Costs

Now in its ninth year, the armed conflict in Nigeria has forced more than 2 million people from their homes, with more than 1.5 million of these displaced within the country. The regionalized conflict – which since 2013 has affected the neighbouring countries of Cameroon, Chad and Niger – has caused a protracted humanitarian crisis with some of the highest human costs in the world. The most affected area in Nigeria is the northeast of the country, primarily the States of Adamawa, Borno and Yobe.

The signature of the planet Mercury in plants

1974 ◽  
Vol 63 (01) ◽  
pp. 26-60
Author(s):  
Agnes Fyfe
Keyword(s):  
Therapeutic Use ◽  
The Moon ◽  
The World ◽  
Plant Test ◽  
Mercury Salts ◽  
The Times ◽  
Future Date ◽  
Plant Sap

Summary• Plant sap tests made at the times of constellations of the planet Mercury show cup forms which are comparable with those that can be produced by adding mercury salts in solution to the gold reagent.• The cup form appears to be specific to the planet Mercury and the metal of the same name.• This connection is demonstrable only as it works in plant saps.• The cup forms appear prior to constellations, disappear during their course and reappear afterwards. These events seem to enhance the forces of the planet.• In cases of doubt, the “true” moment of a constellation can be determined from the plant test.• Constellations are never repeated under the same circumstances in the heavens. Because of this, variations appear each time in the pictures, and the duration of planetary influence on the plant also varies.• Some conditions are favourable, other unfavourable for the observation of the Mercury influence.• Many years' observation of how the world of the stars is reflected in mistletoe sap makes it possible to forecast the probable quality of the sap from plants picked at a future date, so that the most favourable days may be chosen for gathering mistletoe for therapeutic use.Favourable as a rule are: constellations that take place when they can run their course undisturbed by others, and also the times when the planet is at elevation.Unfavourable as a rule: closely following sequences of constellations especially where the Moon is involved and likely to be strong in effect.

Failure Modes Mechanisms Effects Analysis for Refrigeration Device

2013 ◽  
Vol 288 ◽  
pp. 69-74 ◽  
Author(s):  
Ren Xiao Xu ◽  
Yang Liu
Keyword(s):  
Life Cycle ◽  
Failure Modes ◽  
Life Cycle Management ◽  
State Assessment ◽  
Remaining Useful Life ◽  
Automatic Identification ◽  
Health State ◽  
Useful Life ◽  
Using Data ◽  
Fusion Approach

FMMEA (failure mode, mechanisms, and effects analysis) is an effective tool for the life-cycle management of products and devices. We conducted an FMMEA for a refrigeration device at the request of a corporation. This paper demonstrates the process of our analysis of the compressor by employing Ganesan’s methodology. The results are listed in a table, including the physics of failures, risk priorities and parameters for monitoring. This paper also provides health-state assessment approaches based on FMMEA results and values of relevant parameters using fusion approach. Such assessment can be used for remaining useful life (RUL) estimation. Additionally, the paper illustrates our approach of computer-program-based automatic identification of failure using data of parameters retrieved from sensors.

scholarly journals An overview of activation functions used in Neuronal Networks: Application for plant disease diagnosis

2021 ◽  
Vol 10 (1) ◽  
pp. 139-145
Keyword(s):  
Plant Disease ◽  
Transfer Functions ◽  
Activation Function ◽  
Disease Diagnosis ◽  
Plant Diseases ◽  
Automatic Identification ◽  
Relevant Parameter ◽  
Activation Functions ◽  
Crop Fields ◽  
Learning Techniques

Deep learning techniques, particularly Convolutional Neural Networks (CNNs), have led to significant progress in image processing. Many applications in automatic identification of plant diseases have been developed. This work adopts a new approach that focuses on studying a relevant parameter that make a significant impact on the performance of CNNs, namely, the variants of activation function, particularly the most famous used functions and their influence on the model’s performance and accuracy. We will also present the different types of activation functions, which are also called transfer functions. Then, and through a case study application to the plant disease detection, we will have the opportunity to compare the results of these different functions with a graphical presentation using evaluation metrics, such as accuracy functions and loss functions as Binary Cross-Entropy. The training of the models was carried out using a free accessible database of 20,639 photographs, taken both in the laboratory and in real conditions from the crop fields. The data includes three plant species in fifteen distinct classes of combinations [plant, disease], including some healthy plants.

scholarly journals Plant Disease Detection and Localization using GRADCAM

2020 ◽  
Vol 8 (6) ◽  
pp. 3069-3075
Keyword(s):  
Deep Learning ◽  
Plant Disease ◽  
Plant Diseases ◽  
Financial Resources ◽  
Disease Detection ◽  
The World ◽  
Detection And Localization ◽  
Better Than ◽  
Made In

Plant diseases are diseases that change or disrupt its important functions. The reduction in the age at which a plant dies is the main danger of plant diseases. And farmers around the world have to face the challenge of identifying and classifying these diseases and changing their treatments for each disease. This task becomes more difficult when they have to rely on naked eyes to identify diseases due to the lack of proper financial resources. But with the widespread use of smartphones by farmers and advances made in the field of deep learning, researchers around the world are trying to find a solution to this problem. Similarly, the purpose of this paper is to classify these diseases using deep learning and localize them on their respective leaves. We have considered two main models for classification called resnet and efficientnet and for localizing these diseases we have used GRADCAM and CAM. GRADCAM was able to localize diseases better than CAM

scholarly journals Nicotine stomatitis in smokers: a case report

2018 ◽  
Vol 3 (1) ◽  
pp. 58
Author(s):  
Doni MS. Prabowo ◽  
Haris B. Widodo
Keyword(s):  
Case Report ◽  
Salivary Glands ◽  
Medical History ◽  
Smokeless Tobacco ◽  
Hard Palate ◽  
World Population ◽  
Minor Salivary Glands ◽  
White Spots ◽  
The World ◽  
History Of

Objective: The aim of this study is to describe and analyse nicotine stomatitis in smokers. Of the world population that consumes tobacco, Asia and Australia make up 57% of tobacco consumers. Tobacco can be consumed by various ways such as smoked tobacco, commonly known as cigarettes, or smokeless tobacco. Cigarettes are known to cause nicotine stomatitis in the oral cavity.Methods: A 28-year-old man patient came with complaints of white spots on his hard palate. The patient has a medical history of asthma as a child and has been taking salbutamol. The patient has been smoking 3 packs of cigarettes a day since being 16 years old.Results: Nicotine stomatitis that occurs on the hard palate appears as circular reddish shapes on the orifice of minor salivary glands. These lesions are formed from physically irritation caused by smoking. The lesions were benign and reversible.Conclusion: Thought appropriate examination and treatment, these lesions were healed.

scholarly journals Invisibility Cloak using Color Detection and Segmentation with Open CV

2020 ◽  
Vol 9 (4) ◽  
pp. 1621-1624
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Harry Potter ◽  
Invisibility Cloak ◽  
Invisible Cloak ◽  
The World ◽  
Color Detection ◽  
False Sense ◽  
Collective Imagination ◽  
Science Fantasy

Have you ever thought of making visible things invisible, just like the Harry Potter? Have you ever thought how does one supersede backgrounds and add effects in a movie? The cloak was magical and invisible in Harry Potter, the movie. As we know there is no magic and no invisible cloak which exists in the world. It’s all about the graphics tricks. The concept of an invisibility cloak is a mixture of science, fantasy, and the collective imagination. This paper helps to create one’s own ‘Invisibility Cloak’.It will make use of Python and OpenCV module specifically targeting Image Processing and Image Segmentation to create a false sense of invisibility in the frame. It will explore how an object of a specific color or texture can be manipulated using the OpenCV library of python. To achieve this, initially we’ll be capturing and storing the backdrop frame . Thereafter we’ll be identifying the red coloured fabric by making use of the above mentioned algorithms. Then we’ll segment out the red colored fabric by generating a mask and then finally , we’ll generate the final augmented(magical) output to create Invisibility cloak. These steps are discussed deeper in the paper

scholarly journals Versatility of the estlander flap: upper lip, lower lip and comissure reconstruction due to a dog bite

2019 ◽  
Vol 7 (6) ◽  
pp. 2428
Author(s):  
Natalia Haro Alvarez ◽  
Jose de Jesus Orozco Grados ◽  
Enrique Chavez Serna ◽  
Alejandro Lopez Garibay ◽  
David Navarro Barquin ◽  
...  
Keyword(s):  
Medical Community ◽  
Dog Bite ◽  
Upper Lip ◽  
Lower Lip ◽  
Lip Reconstruction ◽  
Affected Area ◽  
Dog Bites ◽  
The World ◽  
Efficient Alternative ◽  
Recovery Assessment

Background: Dog bites continue to be a frequent cause for plastic and reconstructive services in the world. The grand majority of these cases affect the head and neck area; and more often than not they involve the commissure and the lips. The latter leading to an increased level of difficulty and a substantial decrease on the posibilities for a successful reconstruction. This case report focuses on the exploration of the Abbe-Estlander flap as an efficient alternative in most of these cases.Methods: We present two clinical cases involving dog bites where the affected area of both patients was estimated to be one third of the total volume of the lip. Both patients required emergency reconstructive surgery. An Estlander flap was successfully performed in both instances. The purpose of the article is to share the results and motivate the medical community to continue to use this method as a strong avenue for an effective recovery.Results: After two months of the surgery, the team followed up with both patients and they were satisfied with the results. Patient A presented adequate healing of the wound; a lack of alignment of the mucocutaneous rim and rounding of the commissure was observed. Phonation, oral continence without any leakage and complete closure of the lip were also part of the recovery assessment. Patient B presented adequate healing of the wound, phonation and medium oral continence with occasional leakage of liquids and incomplete closure.Conclusions: The Abbe-Estlander flap is still an excellent reconstructive alternative for upper and lower lip reconstruction where the affected area is up to one third of the total volume. As long as the commissure involvement represents minimum difficulty, both aesthetic and functional objectives can be successfully attained using this flap.

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