Vandana Malode

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James Elkins

School of the Art Institute of Chicago

Maurizio Forte

Duke University

David Seamon

Kansas State University

Hanung Adi Nugroho

Universitas Gadjah Mada (Yogyakarta)

Moncef Gabbouj

Tampere University

Fabio Cuzzolin

Oxford Brookes University

Athanasios Ι. Margaris

University of Thessaly

Pablo Alvarez-Alonso

University of Oviedo / Universidad de Oviedo

Md Kafiul Islam

Independent University, Bangladesh

Rodrigo SALAS

Universidad de Valparaiso

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Lung Cancer Analysis and Diagnosis by Coalition of Photo Metric and Quality Metric Parameters

2020 International Conference on Emerging Smart Computing and Informatics (ESCI), 2020

Lung cancer still seems to be a very common cause of death among the people all over the world. T... more Lung cancer still seems to be a very common cause of death among the people all over the world. This paper proposes a method which is a coalition of two statistical methods Photo Metric and Quality Metric enacted for lung cancer analysis and diagnosis. Suggested methodology is established on the basis of identified statistical and mathematical parameters exploring the light variation and quality features of the lung image to carry out the evaluation for cancerous and non-cancerous types. The distinguishing Photo Metric parameters are Brightness, Luminance, Contrast and LC index, whereas the Quality Metric parameters are VIF, MSE, VSNR and PSNR. These eight identified parameters are applied one by one on the cancerous and noncancerous lung images using image processing technique using MATLAB to get an individual parameter statistical range through number of iterations in real time. If the test image falls in the particular calculated statistical range for cancerous lung images, then the test image is infected or else normal. But practically some of the values of the statistical range for cancerous and noncancerous lungs overlaps due to which the final decision is taken by an image classifier. The ANN is used as an image classifier to sort out this problem resulting in an efficient lung cancer diagnosis. The microscopic lung images are used to implement the proposed methodology. The performance analysis of each identified parameter is the heart of this paper. The authentication of the proposed methods is tested successfully using Standard Diagnostic Test.

Automatic Soil Testing System

2020 International Conference on Smart Innovations in Design, Environment, Management, Planning and Computing (ICSIDEMPC)

Soil is a vital, living component of the environment–a component that can be manipulated to affec... more Soil is a vital, living component of the environment–a component that can be manipulated to affect crop performance. Soil contains vital nutrients, NPK (Nitrogen, Phosphorous and Potassium) contents and pH which are necessary for successful growth of plants. But this testing is very painful process for the farmers because, farmer need to bring that soil to testing lab and testing takes more than 4-5 days to complete process. And cost of soil testing is also high so poor farmers can’t afford it so they avoid to soil testing. The main aim of this proof of concept model is to construct a soil nutrient testing kit using Arduino UNO board and sensor module. This project gives the details regarding the amount of macro-nutrients and micro-nutrients present in the given sample of soil. The pH value and electrical conductivity of the soil are also measured. From the electrical conductivity we are estimating the salinity of soil and water drainage in the field. All this information regarding the soil which help to determine the which type of crop that can grown more effectively in same soil.

New approach of statistical analysis for lung disease diagnosis using microscopy images

2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT), 2016

Lungs play an important role in human respiratory system. There are various diseases that effect ... more Lungs play an important role in human respiratory system. There are various diseases that effect the functioning of the lungs. Diagnosis and treatment of the disease is most important for proper functioning of human body. The most difficult part is to detect and diagnose the diseases at primary stage. In this paper, a computerized method for lung disease diagnosis is implemented. The lung diseases like Fibrosis, Emphysema and lung Cancer is detected using MATLAB software as these diseases are having almost similar symptoms and hence difficult to diagnose. The algorithm implemented here is based on Texture analysis, Principle Components Analysis and various image quality measurement statistical parameters such as Entropy, Standard Deviation and Texture index. Fuzzy logic is used to calculate the performance parameters of lung images. The algorithm is implemented and tested on microscopy lung images

Tomato Leaf Disease Detection and Classification using Convolution Neural Network

2021 International Conference on Emerging Smart Computing and Informatics (ESCI), 2021

Mostly development of country depends of growth of agriculture sectors. Now a day agriculture is ... more Mostly development of country depends of growth of agriculture sectors. Now a day agriculture is facing lot of challenges like unavailability of labor, drastic climate change, uncertainty in rain, natural disaster, different diseases on plant leaf and crops, no fixed prices and unavailability of markets and many more. But as the world continuously increasing the demands of food and more production needed in next 50 years. There are huge numbers of threats in agriculture field. The use of artificial intelligence technology, found best for the all agriculture challenges. So our proposed research focus on detecting and classifying the accurate type of diseases occurred on leaf at early stage. Our research aims to address the problem using the Deep Learning (DL) techniques. The AgroDeep mobile application developed for collection of real database of agriculture leafs and crop. The real diseased leaf images collected and captured through our mobile application. The captured images uploaded over database. There are total six types of crops leaf images (tomato, grapes, soybean, sugarcane, cotton and onion) collected. The tomato diseased leaf selected for detection and classification. The techniques supported whether diseases affected on leaf or not with percentage of accuracy. The best Convolution Neural Network (CNN) algorithm suitable for these analysis. The CNN based model gave the highest accuracy of 97 % which is highest forever for real captured diseased images. Our research playing exquisite role in agriculture sector and farmers. The proposed research supported to increase food production in the agriculture. Ultimately it gives more profit in the farming sector which motivate the farmers for agriculture.

Move ovement ove ment Based Voice Enabled nabled Robotic Chair for Physically hysically Challenged hallenged

There are lots of handicaps and elders in the world. Many of them are not able to move as easily ... more There are lots of handicaps and elders in the world. Many of them are not able to move as easily as normal people. It is useful if we develop an automatic wheelchair to help them move more freely. In this paper we proposed a design of smallarea automatic wheelchair to help handicaps or elders are able to move easily in a small area. The most concern in this project is low cost with acceptable performance rather than high velocity or high accuracy. The main aim of this project is to control the devices and to ask the basic needs like water, food or medicine by using MEMS (Micro Electro-Mechanical Systems) technology. MEMS is a Sensor which is a highly sensitive sensor and capable of detecting the tilt. This sensor finds the tilt is to the right side then the device will be on for the first time then next time it will be off. In the same way, if the tilt is to the left side then another device is going to be controlled. The tilt is in upwards or downward direction the related need wil...

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