Blar i SINTEF Digital på forfatter "Uddin, Md Zia"
-
Active sense: Early staging of non-insulin dependent diabetes mellitus (niddm) hinges upon recognizing daily activity pattern
Bahadur, Erfanul Hoque; Masum, Abdul Kadar Muhammad; Barua, Arnab; Uddin, Md Zia (Peer reviewed; Journal article, 2021)The Human Activity Recognition (HAR) system allows various accessible entries for the early diagnosis of Diabetes as one of the nescient applications domains for the HAR. Long Short-Term Memory (LSTM) was applied and ... -
An Analysis of Data Production Based on the Consistency of Decision Matrices
Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia; Soylu, Ahmet (Peer reviewed; Journal article, 2021)Multi-criteria decision making methods are used to solve numerous problems related to several disciplines such as engineering, management and business. Consistency of a decision making application is of crucial importance ... -
Classification of Individual Finger Movements from Right Hand Using fNIRS Signal
Khan, Haroon; Noori, Farzan Majeed; Yazidi, Anis; Uddin, Md Zia; Khan, M.N Afzal; Mirtaheri, Peyman (Peer reviewed; Journal article, 2021)Functional near-infrared spectroscopy (fNIRS) is a comparatively new noninvasive, portable, and easy-to-use brain imaging modality. However, complicated dexterous tasks such as individual finger-tapping, particularly using ... -
CNN-XGBoost fusion-based affective state recognition using EEG spectrogram image analysis
Khan, Md. Sakib; Salsabil, Nishat; Alam, Md. Golam Rabiul; Dewan, M. Ali Akber; Uddin, Md Zia (Peer reviewed; Journal article, 2022)Recognizing emotional state of human using brain signal is an active research domain with several open challenges. In this research, we propose a signal spectrogram image based CNN-XGBoost fusion method for recognising ... -
Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor
Khatun, Mst. Alema; Yousuf, Mohammad Abu; Ahmed, Sabbir; Uddin, Md Zia; Alyami, Salem A.; Al-Ashhab, Samer; Akhdar, Hanan F.; Khan, Asaduzzaman; Azad, Akm; Moni, Mohammad Ali (Peer reviewed; Journal article, 2022)Human Activity Recognition (HAR) systems are devised for continuously observing human behavior - primarily in the fields of environmental compatibility, sports injury detection, senior care, rehabilitation, entertainment, ... -
Deep learning for prediction of depressive symptoms in a large textual dataset
Uddin, Md Zia; Dysthe, Kim Kristoffer; Følstad, Asbjørn; Brandtzæg, Petter Bae (Peer reviewed; Journal article, 2021)Depression is a common illness worldwide with potentially severe implications. Early identification of depressive symptoms is a crucial first step towards assessment, intervention, and relapse prevention. With an increase ... -
Delicar: A smart deep learning based self driving product delivery car in perspective of Bangladesh
Chy, Md. Kalim Amzad; Masum, Abdul Kadar Muhammad; Sayeed, Kazi Abdullah Mohammad; Uddin, Md Zia (Peer reviewed; Journal article, 2022)The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it ... -
Emotion recognition using speech and neural structured learning to facilitate edge intelligence
Uddin, Md Zia; Nilsson, Erik Gøsta (Peer reviewed; Journal article, 2020)Emotions are quite important in our daily communications and recent years have witnessed a lot of research works to develop reliable emotion recognition systems based on various types data sources such as audio and video. ... -
Estimation of mechanical power output employing deep learning on inertial measurement data in roller ski skating
Uddin, Md Zia; Seeberg, Trine Margrethe; Kocbach, Jan; Liverud, Anders E.; Gonzalez, Victor; Sandbakk, Øyvind; Meyer, Frederic (Peer reviewed; Journal article, 2021)The ability to optimize power generation in sports is imperative, both for understanding and balancing training load correctly, and for optimizing competition performance. In this paper, we aim to estimate mechanical power ... -
Estimation of mechanical power output employing deep learning on inertial measurement data in roller ski skating
Uddin, Md Zia; Seeberg, Trine Margrethe; Kocbach, Jan; Liverud, Anders E.; Gonzalez, Victor; Sandbakk, Øyvind; Meyer, Frederic (Peer reviewed; Journal article, 2021)The ability to optimize power generation in sports is imperative, both for understanding and balancing training load correctly, and for optimizing competition performance. In this paper, we aim to estimate mechanical power ... -
Human activity recognition using wearable sensors, discriminant analysis, and long short-term memory-based neural structured learning
Uddin, Md Zia; Soylu, Ahmet (Peer reviewed; Journal article, 2021)Healthcare using body sensor data has been getting huge research attentions by a wide range of researchers because of its good practical applications such as smart health care systems. For instance, smart wearable sensor-based ... -
Monitoring In-Home Emergency Situation and Preserve Privacy using Multi-modal Sensing and Deep Learning
Bordvik, David Andreas; Hou, Jie; Noori, Farzan Majeed; Uddin, Md Zia; Tørresen, Jim (Chapter, 2022)Videos and images are commonly used in home monitoring systems. However, detecting emergencies in-home while preserving privacy is a challenging task concerning Human Activity Recognition (HAR). In recent years, HAR combined ... -
On Converting Crisp Failure Possibility into Probability for Reliability of Complex Systems
Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia; Soylu, Ahmet (Peer reviewed; Journal article, 2021)The reliability of complex systems is analyzed based on several systematic steps using many safety engineering methods. The most common technique for safety system analysis and reliability, vulnerability and criticality ... -
Ultra-Wideband Radar-Based Activity Recognition Using Deep Learning
Noori, Farzan Majeed; Uddin, Md Zia; Tørresen, Jim (Peer reviewed; Journal article, 2021)With recent advances in the field of sensing, it has become possible to build better assistive technologies. This enables the strengthening of eldercare with regard to daily routines and the provision of personalised care ... -
Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography
Islam, Md Nazmul; Hasan, Mehedi; Hossain, Md Kabir; Alam, Md Golam Rabiul; Uddin, Md Zia; Soylu, Ahmet (Peer reviewed; Journal article, 2022)Renal failure, a public health concern, and the scarcity of nephrologists around the globe have necessitated the development of an AI-based system to auto-diagnose kidney diseases. This research deals with the three major ...