Search Results - (( model prediction models algorithm ) OR ( image classification system algorithm ))

Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
Get full text
Get full text
Get full text

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…In conclusion, hybrid DNN with the K-Means Clustering Algorithm is proven to resolve parameter estimations of the chaotic system by developing an accurate prediction model.…”
Get full text
Get full text

Leaf condition analysis using convolutional neural network and vision transformer by Yong, Wai Chun, Ng, Kok Why, Haw, Su Cheng, Naveen, Palanichamy, Ng, Seng Beng

“…Since the performance of the models is determined on the overall quality of the dataset, this could compromise the predictive models. …”
Get full text
Get full text
Get full text

AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION by LAW, JIN MING

“…The prediction results in classification accuracy of 100%. …”
Get full text
Get full text
Get full text

A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function by Yap K.S., Lim C.P., Abidin I.Z.

Subjects:

Development of vehicle counting system by using background subtraction technique / Muhammad Fadhli Md Azemin by Md Azemin, Muhammad Fadhli

“…With a view to improvement, it is proposed to develop a unique algorithm for vehicle classification and counting using Gaussian Mixture Model (GMM) and blob analysis method. …”
Get full text
Get full text

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
Get full text
Get full text

Classification of microcalcification in mammogram images using Enhanced Support Vector Machine (ESVM) / Muhammad Akmal Firdaus... [et al.] by Firdaus, Muhammad Akmal, Shadan, Siti Madinah, Mohd Faudzai, Nur Syahizah

“…Support Vector Machine (SVM) is a supervised machine learning algorithm with the ability to build a classification model from a labeled dataset. …”
Get full text
Get full text

Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Mohamed, Shakir, Qidwai, Uvais, Malik, Aamir Saeed, Kamel , Nidal

“…The model has been validated and tested with respect to accuracy of correct regeneration, false prediction rate, specificity, sensitivity and false detection rate.…”
Get full text
Get full text

Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

“…Principal component analysis was used to develop quantitative prediction models and clustering ability of three different varieties of pineapples. …”
Get full text
Get full text

Prediction of breast cancer diagnosis using machine learning in Malaysian women by Mokhtar, Tengku Muhammad Hanis Tengku

“…Eight ML algorithms were explored in this project. k-nearest neighbour (kNN) models had a significantly better performance compared to the other seven models. …”
Get full text
Get full text

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
Get full text
Get full text
Get full text

EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Shakir, Mohamed, Qidwai, Uvais, Malik, Aamir Saeed, Kamel, Nidal

“…The model has been validated and tested with respect to accuracy of correct regeneration, false prediction rate, specificity, sensitivity and false de-tection rate…”
Get full text
Get full text

Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

“…The accuracy of the CNN model is comparable with the accuracy of the previous work that utilizing CNN for the imaging data to detect caries (diagnostic tool).…”
Get full text
Get full text

Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
Get full text
Get full text
Get full text

Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Fatimah, Dzaharudin, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

“…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
Get full text
Get full text
Get full text

Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps by Song-Quan Ong, Toke Thomas Høye

“…Using a generalised linear model (GLM) and a Boruta feature selection algorithm, we also showed that the colour and architecture of the sticky traps significantly influenced the performance of the model. …”
Get full text
Get full text
Get full text

Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
Get full text
Get full text
Get full text
Get full text

Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique) by Zubir, Nazira

“…The examples of image processing and classification techniques used for predicting lung cancer are summarized. …”
Get full text
Get full text

Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process by Jahedsaravani, A., Massinaei, Mohammad, Marhaban, Mohammad Hamiruce

“…The classification of the images is actually necessary to determine the ideal froth structure and the target set-points for a machine vision control system. …”
Get full text
Get full text
Get full text