85 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Mississippi State UniversityUS5 papers
- Islamic University of TechnologyBD4 papers
- University of HyogoJP4 papers
- Vanderbilt UniversityUS4 papers
- BRAC UniversityBD3 papers
- Rajshahi University of Engineering and TechnologyBD3 papers
- North South UniversityBD2 papers
- Ahsanullah University of Science and TechnologyBD1 paper
- Bangladesh University of Engineering and TechnologyBD1 paper
- Deakin UniversityAU1 paper
- Dhaka University of Engineering & TechnologyBD1 paper
- Jagannath UniversityIN1 paper
21 papers
Hybridized Convolutional Neural Networks and Long Short-Term Memory for Improved Alzheimer's Disease Diagnosis from MRI Scans
Maleka Khatun, Md Manowarul Islam, Habibur Rahman Rifat +3
Brain-related diseases are more sensitive than other diseases due to several factors, including the complexity of surgical procedures, high costs, and other challenges. Alzheimer's…
CEIMVEN: An Approach of Cutting Edge Implementation of Modified Versions of EfficientNet (V1-V2) Architecture for Breast Cancer Detection and Classification from Ultrasound Images
Sheekar Banerjee, Md. Kamrul Hasan Monir
Undoubtedly breast cancer identifies itself as one of the most widespread and terrifying cancers across the globe. Millions of women are getting affected each year from it. Breast…
AutoCl : A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance
Fuad Ahmed, Rubayea Ferdows, Md Rafiqul Islam +1
Nowadays, deep learning (DL) models being increasingly applied to various fields, people without technical expertise and domain knowledge struggle to find an appropriate model for…
Using Spatio-temporal Deep Learning for Forecasting Demand and Supply-demand Gap in Ride-hailing System with Anonymised Spatial Adjacency Information
M. H. Rahman, S. M. Rifaat
To reduce passenger waiting time and driver search friction, ride-hailing companies need to accurately forecast spatio-temporal demand and supply-demand gap. However, due to spatio…
Prediction of Temperature and Rainfall in Bangladesh using Long Short Term Memory Recurrent Neural Networks
Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Shadman Sakib +3
Temperature and rainfall have a significant impact on economic growth as well as the outbreak of seasonal diseases in a region. In spite of that inadequate studies have been carrie…
Electrocardiogram Heartbeat Classification Using Convolutional Neural Networks for the Detection of Cardiac Arrhythmia
Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Shadman Sakib +3
The classification of the electrocardiogram (ECG) signal has a vital impact on identifying heart-related diseases. This can ensure the premature finding of heart disease and the pr…
Deep Convolutional Neural Networks Model-based Brain Tumor Detection in Brain MRI Images
Md. Abu Bakr Siddique, Shadman Sakib, Mohammad Mahmudur Rahman Khan +3
Diagnosing Brain Tumor with the aid of Magnetic Resonance Imaging (MRI) has gained enormous prominence over the years, primarily in the field of medical science. Detection and/or p…
Performance Evaluation of t-SNE and MDS Dimensionality Reduction Techniques with KNN, ENN and SVM Classifiers
Shadman Sakib, Md. Abu Bakr Siddique, Md. Abdur Rahman
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 Multidimens…
Performance Analysis of Deep Autoencoder and NCA Dimensionality Reduction Techniques with KNN, ENN and SVM Classifiers
Md. Abu Bakr Siddique, Shadman Sakib, Md. Abdur Rahman
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…
Non-Intrusive Electrical Appliances Monitoring and Classification using K-Nearest Neighbors
Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Shadman Sakib
Non-Intrusive Load Monitoring (NILM) is the method of detecting an individual device's energy signal from an aggregated energy consumption signature [1]. As existing energy meters…
Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layers
Fathma Siddique, Shadman Sakib, Md. Abu Bakr Siddique
In recent times, with the increase of Artificial Neural Network (ANN), deep learning has brought a dramatic twist in the field of machine learning by making it more artificially in…
Implementation of Fruits Recognition Classifier using Convolutional Neural Network Algorithm for Observation of Accuracies for Various Hidden Layers
Shadman Sakib, Zahidun Ashrafi, Md. Abu Bakr Siddique
Fruit recognition using Deep Convolutional Neural Network (CNN) is one of the most promising applications in computer vision. In recent times, deep learning based classifications a…
Modeling and Simulation of Solar Photovoltaic Cell for the Generation of Electricity in UAE
Shadman Sakib, Md. Abu Bakr Siddique
This paper proposes the implementation of a circuit based simulation for a Solar Photovoltaic (PV) cell in order to get the maximum power output. The model is established based on…
Unsupervised Segmentation Algorithms' Implementation in ITK for Tissue Classification via Human Head MRI Scans
Shadman Sakib, Md. Abu Bakr Siddique
Tissue classification is one of the significant tasks in the field of biomedical image analysis. Magnetic Resonance Imaging (MRI) is of great importance in tissue classification es…
Negative Impact and Probable Management Policy of E-Waste in Bangladesh
S. M. Rezaul Karim, Shariful Islam Sharif, Md. Anisur Rahman Anik
Due to the wider usage of electrical and electronic products throughout the country, Electronic waste (E-waste) is growing and creating problems. E-waste contains toxic materials w…
Implementation of Fuzzy C-Means and Possibilistic C-Means Clustering Algorithms, Cluster Tendency Analysis and Cluster Validation
Md. Abu Bakr Siddique, Rezoana Bente Arif, Mohammad Mahmudur Rahman Khan +1
In this paper, several two-dimensional clustering scenarios are given. In those scenarios, soft partitioning clustering algorithms (Fuzzy C-means (FCM) and Possibilistic c-means (P…
ADBSCAN: Adaptive Density-Based Spatial Clustering of Applications with Noise for Identifying Clusters with Varying Densities
Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Rezoana Bente Arif +1
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…
Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Neural Network Algorithm
Md. Abu Bakr Siddique, Mohammad Mahmudur Rahman Khan, Rezoana Bente Arif +1
In recent days, Artificial Neural Network (ANN) can be applied to a vast majority of fields including business, medicine, engineering, etc. The most popular areas where ANN is empl…
Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Convolutional Neural Network
Rezoana Bente Arif, Md. Abu Bakr Siddique, Mohammad Mahmudur Rahman Khan +1
Nowadays, deep learning can be employed to a wide ranges of fields including medicine, engineering, etc. In deep learning, Convolutional Neural Network (CNN) is extensively used in…
Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository
Mohammad Mahmudur Rahman Khan, Rezoana Bente Arif, Md. Abu Bakr Siddique +1
Machine learning qualifies computers to assimilate with data, without being solely programmed [1, 2]. Machine learning can be classified as supervised and unsupervised learning. In…
Real-time Surgical Tools Recognition in Total Knee Arthroplasty Using Deep Neural Networks
Moazzem Hossain, Soichi Nishio, Takafumi Hiranaka +1
Total knee arthroplasty (TKA) is a commonly performed surgical procedure to mitigate knee pain and improve functions for people with knee arthritis. The procedure is complicated du…