scholarly journals Identifikasi Tuberkulosis Paru Berdasarkan Foto Sinar-X Thorax Menggunakan Jaringan Syaraf Tiruan Backpropagation

2021 ◽  
Vol 17 (1) ◽  
pp. 27
Author(s):  
Qahtan Said ◽  
Iin Ernawati ◽  
Mayanda Mega Santoni
Keyword(s):  
Gabor Filter ◽  
Levenberg Marquardt

Pengobatan TB tidaklah mudah, pendiagnosaan TB membutuhkan ketelitian yang tinggi. Penelitian ini bertujuan untuk melihat perbandingan performa dari GLCM, Gabor Filter dan gabungan dalam mengidentifikasi tuberkulosis paru dengan metode pengolahan citra digital yang terdiri dari beberapa tahap. Tahapan-tahapan tersebut dimulai dengan mengumpulkan citra Sinar-X paru dari bank data NLM sebanyak 662 citra lalu dilakukan pemilihan citra yang berhasil tersegmentasi saja, yaitu sebanyak 558 citra. Kemudian citra masukan tersebut akan dilakukan peningkatan kualitas citra, segmentasi, ekstraksi RoI, ekstraksi fitur tekstur GLCM dan Gabor Filter, lalu mengklasifikasikan citra dengan dua kelas yaitu : tuberkulosis dan normal menggunakan jaringan syaraf tiruan Backpropagation Levenberg Marquardt. Setelah dilakukan uji performa dengan beberapa percobaan, performa terbaik didapat dengan menggunakan ekstraksi ciri fitur GLCM + Gabor Filter (gabungan) dengan rata-rata accuracy sebesar 84.82%, precission sebesar 86.13%, dan recall sebesar 83.48%. Penelitian ini diharapkan dapat menjadi referensi para peneliti lain untuk menentukan model pengidentifikasian TB paru yang tepat.

Balanço de radiação utilizando métodos de estimativa da radiação solar em cultivo de cana-de-açúcar

Agrometeoros ◽  
2020 ◽  
Vol 27 (1) ◽  
Author(s):  
Joana Madeira Krieger ◽  
Isabella Siqueira Vieira ◽  
Wellerson De Oliveira Alves da Silva ◽  
José Leonaldo Souza ◽  
Guilherme Bastos Lyra ◽  
...  
Keyword(s):  
Levenberg Marquardt

 Devido à dificuldade de medidas contínuas e de qualidades das componentes do balanço de radiação, existe a necessidade de desenvolver modelos para estimá-las. Este trabalho ajustou os coeficientes dos métodos de Hargreaves-Samani (HaS) e Bristow-Campbell (BrC) para estimava da radiação solar global (Rs), assim como o albedo (α) e os coeficientes de um modelo de balanço de ondas longas (Rnl) em cultivo de cana-de açúcar na região de Rio Largo/AL. Medições das componentes do balanço (Rn) de radiação foram realizadas no período de 03 a 27/06/2006 por um saldo radiômetro. Os coeficientes foram ajustados por meio de técnicas de problemas inversos (Levenberg-Marquardt). Após o ajuste, os modelos de balanço de ondas curtas (Rns), Rnl e Rn obtidos em função de Rs estimado por HaS e BrC foram comparados com observações dessas componentes. O método de BrC ajustado (β0 = 0,478, β1 = 0,016 e β2 = 2,78) teve maior precisão e exatidão que o método de HaS (kt = 0,172). Os métodos de Rs ajustados quando usados na estimava de Rns, Rnl e Rn tiveram estimativas acuradas. Os erros dos modelos quando usados Rs estimados por HaS e BrC foram em sua maioria, repasse dos erros obtidos na estimativa de Rs. Entretanto, os erros dos modelos, principalmente do Rnl, têm baixo impacto no Rn.

IMAGE THRESHOLDING BASED ON HIERARCHICAL CLUSTERING ANALYSIS AND PERCENTILE METHOD FOR TUNA IMAGE SEGMENTATION

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Alifia Puspaningrum ◽  
Nahya Nur ◽  
Ozzy Secio Riza ◽  
Agus Zainal Arifin
Keyword(s):  
Image Segmentation ◽  
Hierarchical Clustering ◽  
Gabor Filter ◽  
Hierarchical Cluster ◽  
Experimental Result ◽  
Main Process ◽  
Percentile Method ◽  
Cluster Analysis Method ◽  
2D Gabor Filter

Automatic classification of tuna image needs a good segmentation as a main process. Tuna image is taken with textural background and the tuna’s shadow behind the object. This paper proposed a new weighted thresholding method for tuna image segmentation which adapts hierarchical clustering analysisand percentile method. The proposed method considering all part of the image and the several part of the image. It will be used to estimate the object which the proportion has been known. To detect the edge of tuna images, 2D Gabor filter has been implemented to the image. The result image then threshold which the value has been calculated by using HCA and percentile method. The mathematical morphologies are applied into threshold image. In the experimental result, the proposed method can improve the accuracy value up to 20.04%, sensitivity value up to 29.94%, and specificity value up to 17,23% compared to HCA. The result shows that the proposed method cansegment tuna images well and more accurate than hierarchical cluster analysis method.

Gabor filter fusion network for pavement crack detection

2020 ◽  
Vol 13 (6) ◽  
pp. 1-9
Author(s):  
CHEN Xiao-Dong ◽  
◽  
AI Da-Hang ◽  
ZHANG Jia-Chen ◽  
CAI Huai-Yu ◽  
...  
Keyword(s):  
Crack Detection ◽  
Gabor Filter ◽  
Pavement Crack Detection

Comparison of an Artificial Neural Network and a Multiple Linear Regression in Predicting the Heat of Combustion of Diesel Fuel Based on Hydrocarbon Groups

2020 ◽  
Vol 71 (6) ◽  
pp. 66-74
Author(s):  
Younis M. Younis ◽  
Salman H. Abbas ◽  
Farqad T. Najim ◽  
Firas Hashim Kamar ◽  
Gheorghe Nechifor
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Diesel Fuel ◽  
Back Propagation ◽  
Second Step ◽  
Heating Value ◽  
Network Training ◽  
Marquardt Algorithm ◽  
Levenberg Marquardt ◽  
Propagation Network

A comparison between artificial neural network (ANN) and multiple linear regression (MLR) models was employed to predict the heat of combustion, and the gross and net heat values, of a diesel fuel engine, based on the chemical composition of the diesel fuel. One hundred and fifty samples of Iraqi diesel provided data from chromatographic analysis. Eight parameters were applied as inputs in order to predict the gross and net heat combustion of the diesel fuel. A trial-and-error method was used to determine the shape of the individual ANN. The results showed that the prediction accuracy of the ANN model was greater than that of the MLR model in predicting the gross heat value. The best neural network for predicting the gross heating value was a back-propagation network (8-8-1), using the Levenberg�Marquardt algorithm for the second step of network training. R = 0.98502 for the test data. In the same way, the best neural network for predicting the net heating value was a back-propagation network (8-5-1), using the Levenberg�Marquardt algorithm for the second step of network training. R = 0.95112 for the test data.

Gabor filter approximation through a Neural Network applied to fingerprint images

2016 ◽  
Author(s):  
Airam Carlos Pais Barreto Marques ◽  
Antonio Carlos Gay Thomé
Keyword(s):  
Neural Network ◽  
Gabor Filter ◽  
Filter Approximation

scholarly journals Fuzzified Circular Gabor Filter for Circular and Near-Circular Object Detection

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 96706-96713 ◽  
Author(s):  
Vladimir Tadic ◽  
Akos Odry ◽  
Attila Toth ◽  
Zoltan Vizvari ◽  
Peter Odry
Keyword(s):  
Object Detection ◽  
Gabor Filter ◽  
Circular Object ◽  
Circular Gabor Filter
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