Mahmudul Hasan

Comilla University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Yoshinori Kobayashi

Saitama University

Md. Kamal Uddin

Noakhali Science and Technology University

Meskat Jahan

Comilla University

Yoshinori Kuno

Saitama University

Riku Goto

Saitama University

Junichi Hanawa

Saitama University

Hisato Fukuda

Saitama University

Sheikh Abujar

Independent University

Syed Akhter Hossain

Daffodil International University

Md. Fazlul Karim Khondakar

Chittagong University of Engineering & Technology

Cooperative Institutions

Weatherford College

301

Rajshahi University of Engineering and Technology

Bangladesh University of Engineering and Technology

University of Dhaka

International Islamic University Chittagong

American International University-Bangladesh

Daffodil International University

University of Rajshahi

Jahangirnagar University

Comilla University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Multimodal Emotion Recognition through Deep Fusion of Audio-Visual Data

Tamanna Sultana Meskat Jahan Md. Kamal Uddin Yoshinori Kobayashi Mahmudul Hasan

The field of emotion recognition in artificial intelligence focuses on enabling machines to comprehend and react to the range of emotions experienced by humans. This paper presents a novel approach that integrates the Convolution Neural Network (CNN) with audio and visual modalities. The study employs the RAVDESS database as a resource to train two distinct models for the analysis of both video and audio data. When it comes to audio pre-processing, advanced signal-processing techniques are applied to extract relevant elements and capture basic acoustic characteristics. A one-dimensional Convolutional Neural Network (CNN) architecture receives the audio data as input, enabling the model to learn complicated patterns and representations from the audio domain. In the context of video pre-processing, sophisticated algorithms are employed to extract essential facial characteristics. In order to capture the changing periods of facial expressions, the video frames are analyzed using a three-dimensional CNN framework following that they have been compressed and converted to grayscale. The fusion technique involves concatenating and extending the outputs of the audio and visual models. The fused features are subsequently sent into a softmax layer, which facilitates the development of a resilient emotion identification system.

Audio visual

Sensor Fusion

10.1109/iccit60459.2023.10441424

Cite

Citations (0)

Automatic Detection and Analysis of Melanoma Skin Cancer using Dermoscopy Images

International Journal of Recent Technology and Engineering (IJRTE) (2019)

Mahmudul Hasan Mohammad Mohsin Md Kamal Hossain Chowdhury

Skin cancer is known as one of the most risky types of cancer. Several kinds of skin cancer, such as melanoma, basal and squamous cell carcinoma, etc., are available. The most unpredictable cancer is melanoma. If we can detect melanoma skin cancer at an early stage, the chances of recovery will be good and we can save many valuable lives. But if we fail to detect early, melanoma can disperse to the different parts of the body and chance of recovery will become difficult. This research presents a developed system to do melanoma diagnosis by using several dermoscopy images. In this research, we preprocessed the images to remove hairs and noises by using some filter techniques such as dull razor technique, median filtering, etc. After that, we segmented the image to find the infected area using some segmentation method and we choose the method that will give us the best results. Then we post-process the images and choose the most infected lesion. After segmentation of the skin lesion, we checked the segmentation accuracy concerning some basic criteria. We compared the segmented skin lesions with the marked skin lesions by a dermatologist. Then we extracted the features of the images of different criteria, such as Asymmetry, Border irregularity, Color variance, Diameter which have the acronym as ABCD. We also analyzed the texture of the lesions and extracted the geometrical features. Finally, we choose decision tree classification methods that gave us the best results.

Dermatoscopy

Skin lesion

10.35940/ijrte.c4561.098319

Cite

Citations (2)

Editors' Introduction: Bangladeshi Anglophone Literature: An Old and Evolving Tradition

Mohammad A. Quayum Mahmudul Hasan

Source

Cite

Citations (0)

A Robust Fuzzy Approach For Gene Expression Data Clustering

Research Square (Research Square) (2021)

Meskat Jahan Mahmudul Hasan

Abstract In the big data era, clustering is one of the most popular data mining method. The majority of clustering algorithms have complications like automatic cluster number determination, poor clustering precision, inconsistent clustering of various datasets and parameter-dependent etc. A new fuzzy autonomous solution for clustering named Meskat-Mahmudul (MM) clustering algorithm proposed to overcome the complexity of parameter–free automatic cluster number determination and clustering accuracy. MM clustering algorithm finds out the exact number of clusters based on Average Silhouette method in multivariate mixed attribute dataset, including real-time gene expression dataset and dealt missing values, noise and outliers. MM Extended K-Means (MMK) clustering algorithm is an enhancement of the K-Means algorithm, which serves the purpose for automatic cluster discovery and runtime cluster placement. Several validation methods used to evaluate cluster and certify optimum cluster partitioning and perfection. Some datasets used to assess the performance of the proposed algorithms to other algorithms in terms of time complexity and clustering efficiency. Finally, MM clustering and MMK clustering algorithms found superior over conventional algorithms.

Data stream clustering

Single-linkage clustering

k-medians clustering

Clustering high-dimensional data

10.21203/rs.3.rs-547452/v1

Cite

Citations (0)

Impact of Kernel-PCA on Different Features for Person Re-Identification

International Journal of Innovative Technology and Exploring Engineering (2021)

Md. Kamal Uddin Amran Bhuiyan Mahmudul Hasan

In the driving field of computer vision, re-identification of an individual in a camera network is very challenging task. Existing methods mainly focus on strategies based on feature learning, which provide feature space and force the same person to be closer than separate individuals. These methods rely to a large extent on high-dimensional feature vectors to achieve high re-identification accuracy. Due to computational cost and efficiency, they are difficult to achieve in practical applications. We comprehensively analyzed the effect of kernel-based principal component analysis (PCA) on some existing high-dimensional person re-identification feature extractors to solve these problems. We initially formulate a kernel function on the extracted features and then apply PCA, significantly reducing the feature dimension. After that, we have proved that the kernel is very effective on different state-of-the-art high-dimensional feature descriptors. Finally, a thorough experimental evaluation of the reference person re-identification data set determined that the prediction method was significantly superior to more advanced techniques and computationally feasible.

Kernel (algebra)

Identification

Feature (linguistics)

Feature vector

10.35940/ijitee.k9457.09101121

Cite

Citations (1)

Tracking People Using Ankle-Level 2D LiDAR for Gait Analysis

Advances in intelligent systems and computing (2020)

Mahmudul Hasan Junichi Hanawa Riku Goto Hisato Fukuda Yoshinori Kuno

Obligation

Tracking (education)

10.1007/978-3-030-51328-3_7

Cite

Citations (12)

UCSB_UCR_VCG TRECVID 2012.

TRECVID (2012)

Santhoshkumar Sunderrajan Mahmudul Hasan Niloufar Pourian Yingying Zhu B. S. Manjunath

Source

Cite

Citations (0)

Stress Detection and Audio-Visual Stimuli Classification from Electroencephalogram

IEEE Access (2024)

Trishita Ghosh Troyee Mehdi Hasan Chowdhury Md. Fazlul Karim Khondakar Mahmudul Hasan Md. Azad Hossain

Audio visual

10.1109/access.2024.3471590

Cite

Citations (1)

Bengali Text generation Using Bi-directional RNN

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2019)

Sheikh Abujar Abu Kaisar Mohammad Masum S. Chowdhury Mahmudul Hasan Syed Akhter Hossain

Current world is growing so fast and communication between nation and different type of people with different language became part of our life. Even from buying product to our social life everything is dependent on communication. Therefore language is the most important part of human life. Though still now there is a language barrier for communication between people. But very soon language will be universal and everyone will be able to communicate in any language worldwide using the NLP technology. For that it is necessary to understand each language individually. This research proposes a new type of text generation of Bangla language using the bi-directional RNN. This technique is used to predict the next possible word in a Bangla text.

Human communication

10.1109/icccnt45670.2019.8944784

Cite

Citations (28)

Table of Contents

Rafiqul Islam Zahidul Islam M. Subbir Parvej MK Rahman Boshir Ahmed

Table (database)

10.1109/icecte57896.2022.10114557

Cite

Citations (0)