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Found 13 papers, 0 papers with code
Prediction of Temperature and Rainfall in Bangladesh using Long Short Term Memory Recurrent Neural Networks
This prediction model can help to understand the weather pattern changes as well as studying seasonal diseases of Bangladesh whose outbreaks are dependent on regional temperature and/or rainfall.
Deep Convolutional Neural Networks Model-based Brain Tumor Detection in Brain MRI Images
Our model can single out the MR images with tumors with an overall accuracy of 96%.
Performance Evaluation of t-SNE and MDS Dimensionality Reduction Techniques with KNN, ENN and SVM Classifiers
The central goal of this paper is to establish two commonly available dimensionality reduction (DR) methods i. e. t-distributed Stochastic Neighbor Embedding (t-SNE) and Multidimensional Scaling (MDS) in Matlab and to observe their application in several datasets.
Performance Analysis of Deep Autoencoder and NCA Dimensionality Reduction Techniques with KNN, ENN and SVM Classifiers
The central aim of this paper is to implement Deep Autoencoder and Neighborhood Components Analysis (NCA) dimensionality reduction methods in Matlab and to observe the application of these algorithms on nine unlike datasets from UCI machine learning repository.
Non-Intrusive Electrical Appliances Monitoring and Classification using K-Nearest Neighbors
Non-Intrusive Load Monitoring (NILM) is the method of detecting an individual device's energy signal from an aggregated energy consumption signature [1].
Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layers
In deep learning, Convolutional Neural Network (CNN) is at the center of spectacular advances that mixes Artificial Neural Network (ANN) and up to date deep learning strategies.
Implementation of Fruits Recognition Classifier using Convolutional Neural Network Algorithm for Observation of Accuracies for Various Hidden Layers
In this paper, a fruit recognition system using CNN is proposed.
Unsupervised Segmentation Algorithms' Implementation in ITK for Tissue Classification via Human Head MRI Scans
Tissue classification is one of the significant tasks in the field of biomedical image analysis.
Implementation of Fuzzy C-Means and Possibilistic C-Means Clustering Algorithms, Cluster Tendency Analysis and Cluster Validation
In this paper, several two-dimensional clustering scenarios are given.
Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository
Upon such accuracy observation, the comparison can be built among KNN, SVM, LMNN, and ENN regarding their performances on each dataset.
Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Convolutional Neural Network
Nowadays, deep learning can be employed to a wide ranges of fields including medicine, engineering, etc.
Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Neural Network Algorithm
The primary objective of this paper is to analyze the influence of the hidden layers of a neural network over the overall performance of the network.
ADBSCAN: Adaptive Density-Based Spatial Clustering of Applications with Noise for Identifying Clusters with Varying Densities
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm which has the high-performance rate for dataset where clusters have the constant density of data points.
