A5072317896- Image and Signal Denoising Methods
- Advanced Image Fusion Techniques
- COVID-19 diagnosis using AI
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Smart Agriculture and AI
- Artificial Intelligence in Healthcare
- Medical Image Segmentation Techniques
- Plant tissue culture and regeneration
- Colorectal Cancer Screening and Detection
- Image Retrieval and Classification Techniques
- Digital Imaging for Blood Diseases
- Brain Tumor Detection and Classification
- Photoacoustic and Ultrasonic Imaging
- IoT-based Smart Home Systems
- Transgenic Plants and Applications
- Diabetes Management and Research
- Spectroscopy and Chemometric Analyses
- Imbalanced Data Classification Techniques
- Diabetes Treatment and Management
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Gastric Cancer Management and Outcomes
- Water Quality Monitoring Technologies
- Advanced X-ray and CT Imaging
- Energy Efficient Wireless Sensor Networks
Mawlana Bhashani Science and Technology University
2016-2025
Jahangirnagar University
2024
Rajshahi Medical College
2021-2024
Regional Medical Center
2021
Bangladesh Institute of Research and Rehabilitation for Diabetes Endocrine and Metabolic Disorders
2021
Gazipur Agricultural University
2017
North South University
2014
University of Warsaw
2013
Flinders University
2012
Waste management leads to the demolition of waste conducted by recycling and landfilling. Deep learning Internet things (IoT) confer an agile solution in classification real-time data monitoring, respectively. This paper reflects a capable architecture system based on deep IoT. The proposed model renders astute way sort digestible indigestible using convolutional neural network (CNN), popular paradigm. scheme also introduces architectural design smart trash bin that utilizes microcontroller...
Gastrointestinal polyps are considered to be the precursors of cancer development in most cases. Therefore, early detection and removal can reduce possibility cancer. Video endoscopy is used diagnostic modality for gastrointestinal polyps. But, because it an operator dependent procedure, several human factors lead misdetection Computer aided polyp miss rate assists doctors finding important regions pay attention to. In this paper, automatic system has been proposed as a support detection....
LoRa (Long-Range) has become the Deoxyribo Nucleic Acid (DNA) of Internet things (IoT) for equipping smart solutions. Home automation is responsible providing a safe and stylish home. This paper proposes capable architecture home both short-range long-range utilizing multiple communication technologies, namely LoRaWAN, server-based gateway, Bluetooth connectivity. integrated system effectively controls distinct types appliances keeps management among all electronics components. A regular...
Breast cancer, lung skin and blood malignancies such as leukemia lymphoma are just a few instances of which is collection cells that proliferate uncontrollably within the body. Acute lymphoblastic one significant form malignancy. The hematologists frequently makes an oversight while determining cancer diagnosis, requires excessive amount time. Thus, this research reflects on novel method for grouping with aid modern technologies like Machine Learning Deep Learning. proposed pipeline occupied...
Diagnosis of COVID-19 positive patients is the eventual move to impede expansion coronavirus. Variations coronavirus make it tough recognize through symptoms. Hence, this research aims at a faster and automatic detection approach disease from chest Computed tomography (CT) scan images. For composition system, constructs feature vector CT images features fusion two Convolutional neural network (CNN) models namely VGG-19 ResNet-50. Before fusion, preprocessing techniques are applied gain more...
Chest X-ray image contains sufficient information that finds wide-spread applications in diverse disease diagnosis and decision making to assist the medical experts. This paper has proposed an intelligent approach detect Covid-19 from chest using hybridization of deep convolutional neural network (CNN) discrete wavelet transform (DWT) features. At first, is enhanced segmented through preprocessing tasks, then CNN DWT features are extracted. The optimum extracted these hybridized minimum...
The COVID-19 pandemic wreaks havoc on healthcare systems all across the world. In scenarios like COVID-19, applicability of diagnostic modalities is crucial in medical diagnosis, where non-invasive ultrasound imaging has potential to be a useful biomarker. This research develops computer-assisted intelligent methodology for lung image classification by utilizing fuzzy pooling-based convolutional neural network FP-CNN with underlying evidence particular decisions. fuzzy-pooling method finds...
Abstract Introduction Diabetes distress (DD) is common and has considerable impacts on diabetes management. Unfortunately, DD less discussed frequently underestimated. This study evaluated the prevalence predictors of in adults with type 2 mellitus (T2DM). Methods A cross-sectional was conducted at several specialized endocrinology outpatient clinics Bangladesh from July 2019 to June 2020; 259 T2DM participated. Participants’ depression were measured using 17-item Distress Scale (DDS-17)...
Inherently ultrasound images are susceptible to noise which leads several image quality issues. Hence, rating of an image's is crucial since diagnosing diseases requires accurate and high-quality images. This research presents intelligent architecture rate the The formulated recognition approach fuses feature from a Fuzzy convolutional neural network (fuzzy CNN) handcrafted extraction method. We implement fuzzy layer in between last max pooling fully connected multiple state-of-the-art CNN...
The gastrointestinal polyp (GIP) is the abnormal growth of tissues in digestive organs. Identifying these polyps from endoscopy video or image a tremendous task to reduce future risk cancer. This paper proposes proper diagnosis method using fusion contourlet transform and fine-tuned VGG19 pre-trained model enhanced endoscopic 224 × patch images. study has used different models (Alexnet, ResNet50, VGG16, VGG19) as well few scratch while works better. Also, this research Principal Component...
Natural Language Processing (NLP) deals with analysing, understanding and generating languages likes human. One of the challenges NLP is training computers to understand way learning using a language as Every session consists several types sentences different context linguistic structures. Meaning sentence depends on actual meaning main words their correct positions. Same word can be used noun or adjective others based position. In NLP, Word Embedding powerful method which trained large...
Chronic kidney disease (CKD) slowly decreases one's ability. A machine learning (ML) based early CKD diagnosis scheme can be an effective solution to reduce this harm. The efficiency of ML techniques depends on the selection and use appropriate features. Hence, research analysis several feature optimization approaches along with a max voting ensemble model establish highly accurate system by using set. is structured five existing classifiers. Three types namely importance, reduction, where...
Concerning the oversight and safeguarding of aquatic environments, it is necessary to ascertain quantity fish, their size, distribution. Many deep learning (DL), artificial intelligence (AI), machine (ML) techniques have been developed oversee safeguard fish species. Still, all previous work had some limitations, such as a limited dataset, only binary class categorization, employing one technique (ML/DL), etc. Therefore, in proposed work, authors develop an architecture that will eliminate...
Paddy cultivation is a significant global economic sector, with rice production playing crucial role in influencing worldwide economies. However, insects paddy farms predominantly impact the growth rate and ecological equilibrium of agricultural field. Hence, precise timely identification settings presents potential strategy for addressing this issue. This study aims to implement an automated system farming by employing realtime framework that incorporates Internet Things (IoT), Blockchain...
Bank loan prediction (BLP) analyzes the financial records of individuals to conclude possible status. Financial always contain confidential information. Hence, privacy is significant in BLP system. This research aims generate a privacy-preserving automated scheme. To achieve this, differential (DP) combined with machine learning (ML). Using benchmark dataset, proposed method two different DP techniques, namely Laplacian and Gaussian, five ML models: Random Forest (RF), Extreme Gradient...