Search Results for author: Shaikh Anowarul Fattah

Found 18 papers, 7 papers with code

A Face Recognition Scheme using Wavelet Based Dominant Features

no code implementations7 Oct 2011 Hafiz Imtiaz, Shaikh Anowarul Fattah

In this paper, a multi-resolution feature extraction algorithm for face recognition is proposed based on two-dimensional discrete wavelet transform (2D-DWT), which efficiently exploits the local spatial variations in a face image.

Face Recognition

A Time-Frequency Domain Approach of Heart Rate Estimation From Photoplethysmographic (PPG) Signal

1 code implementation1 Apr 2017 Mohammad Tariqul Islam, Ishmam Zabir, Sk. Tanvir Ahamed, Md. Tahmid Yasar, Celia Shahnaz, Shaikh Anowarul Fattah

Significance- The proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach and thus feasible for implementing in wearable devices to monitor heart rate for fitness and clinical purpose.

Applications

SPECMAR: Fast Heart Rate Estimation from PPG Signal using a Modified Spectral Subtraction Scheme with Composite Motion Artifacts Reference Generation

1 code implementation15 Oct 2018 Mohammad Tariqul Islam, Sk. Tanvir Ahmed, Celia Shahnaz, Shaikh Anowarul Fattah

In this paper, a fast algorithm for heart rate estimation based on modified SPEctral subtraction scheme utilizing Composite Motion Artifacts Reference generation (SPECMAR) is proposed using two-channel PPG and three-axis accelerometer signals.

Heart rate estimation

ResCovNet: A Deep Learning-Based Architecture For COVID-19 Detection From Chest CT Scan Images

no code implementations17 Nov 2020 Ankan Ghosh Dastider, Mohseu Rashid Subah, Farhan Sadik, Tanvir Mahmud, Shaikh Anowarul Fattah

Automatic disease detection using machine learning-based techniques from X-ray and computed tomography (CT) can play a major role in the frontline to assist medical professionals during the current outbreak of COVID-19.

BIG-bench Machine Learning Computed Tomography (CT)

CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans

no code implementations2 Dec 2020 Tanvir Mahmud, Md Awsafur Rahman, Shaikh Anowarul Fattah, Sun-Yuan Kung

Moreover, a multi-scale fusion module is introduced with a pyramid fusion scheme to reduce the semantic gaps between subsequent encoder/decoder modules while facilitating the parallel optimization for efficient gradient propagation.

COVID-19 Image Segmentation Efficient Neural Network +2

Automatic Diagnosis of Malaria from Thin Blood Smear Images using Deep Convolutional Neural Network with Multi-Resolution Feature Fusion

no code implementations9 Dec 2020 Tanvir Mahmud, Shaikh Anowarul Fattah

In this paper, an end-to-end deep learning-based approach is proposed for faster diagnosis of malaria from thin blood smear images by making efficient optimizations of features extracted from diversified receptive fields.

A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network

no code implementations3 Jan 2021 Tanvir Mahmud, A. Q. M. Sazzad Sayyed, Shaikh Anowarul Fattah, Sun-Yuan Kung

In this paper, we have proposed a novel multi-stage training approach that increases diversity in this feature extraction process to make accurate recognition of actions by combining varieties of features extracted from diverse perspectives.

Human Activity Recognition Time Series +1

CovTANet: A Hybrid Tri-level Attention Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans

no code implementations3 Jan 2021 Tanvir Mahmud, Md. Jahin Alam, Sakib Chowdhury, Shams Nafisa Ali, Md Maisoon Rahman, Shaikh Anowarul Fattah, Mohammad Saquib

A multi-phase optimization strategy is introduced for solving the challenges of complicated diagnosis at a very early stage of infection, where an efficient lesion segmentation network is optimized initially which is later integrated into a joint optimization framework for the diagnosis and severity prediction tasks providing feature enhancement of the infected regions.

Lesion Segmentation Segmentation +1

An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound

1 code implementation1 May 2021 Ankan Ghosh Dastider, Farhan Sadik, Shaikh Anowarul Fattah

The proposed convolutional neural network (CNN) architecture implements an autoencoder network and separable convolutional branches fused with a modified DenseNet-201 network to build a vigorous, noise-free classification model.

severity prediction

DwinFormer: Dual Window Transformers for End-to-End Monocular Depth Estimation

no code implementations6 Mar 2023 Md Awsafur Rahman, Shaikh Anowarul Fattah

In this paper, a dual window transformer-based network, namely DwinFormer, is proposed, which utilizes both local and global features for end-to-end monocular depth estimation.

Monocular Depth Estimation

CIFF-Net: Contextual Image Feature Fusion for Melanoma Diagnosis

no code implementations7 Mar 2023 Md Awsafur Rahman, Bishmoy Paul, Tanvir Mahmud, Shaikh Anowarul Fattah

In this paper, based on contextual image feature fusion (CIFF), a deep neural network (CIFF-Net) is proposed, which integrates patient-level contextual information into the traditional approaches for improved Melanoma diagnosis by concurrent multi-image comparative method.

Melanoma Diagnosis Skin Cancer Classification

Quantum Convolutional Neural Networks with Interaction Layers for Classification of Classical Data

1 code implementation20 Jul 2023 Jishnu Mahmud, Raisa Mashtura, Shaikh Anowarul Fattah, Mohammad Saquib

Quantum Machine Learning (QML) has come into the limelight due to the exceptional computational abilities of quantum computers.

Quantum Machine Learning

Decoding Human Activities: Analyzing Wearable Accelerometer and Gyroscope Data for Activity Recognition

no code implementations3 Oct 2023 Utsab Saha, Sawradip Saha, Tahmid Kabir, Shaikh Anowarul Fattah, Mohammad Saquib

In this paper, a stratified multi-structural approach based on a Residual network ensembled with Residual MobileNet is proposed, termed as FusionActNet.

Activity Recognition

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