Results for “"Mohammad Shoyaib"”

Sadia Sharmin, Mohammad Shoyaib, Amin Ahsan Ali, Muhammad Asif Hossain Khan et al.

Recently mutual information based feature selection criteria have gained popularity for their superior performances in different applications of pattern recognition and machine learning areas. However, these methods do not consider the correction while computing mutual information for finite samples...

Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md Mehedi Hasan et al.

BACKGROUND: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing and understanding genetic regulatory networks. The increased availability of sequence data for various eukaryotic organism...

S.M. Sofiqul Islam, Shanto Rahman, Md. Mostafijur Rahman, Emon Kumar Dey et al.

Deep learning is a new era of machine learning research, where many layers of information processing stages are exploited for unsupervised feature learning. Using multiple levels of representation and abstraction, it helps a machine to understand about data (e.g., images, sound and text) more accura...

Md. Tauhid Bin Iqbal, Mohammad Shoyaib, Byungyong Ryu, M. Abdullah‐Al‐Wadud et al.

An appropriate aging description from face image is the prime influential factor in human age recognition, but still there is an absence of a specially engineered aging descriptor, which can characterize discernible facial aging cues (e.g., craniofacial growth, skin aging) from a detailed and more f...

Khalid Hussain, Shanto Rahman, Md. Mostafijur Rahman, Shah Mostafa Khaled et al.

Abstract Traditional image enhancement techniques produce different types of noise such as unnatural effects, over-enhancement, and artifacts, and these drawbacks become more prominent in enhancing dark images. To overcome these drawbacks, we propose a dark image enhancement technique where local tr...

Shanto Rahman, Md. Mostafijur Rahman, Khalid Hussain, Shah Mostafa Khaled et al.

With the advancement of imaging science, image enhancement has become an important aspect of image processing domain. It is necessary to gather a comprehensive knowledge regarding the existing enhancement technologies to identify and solve their problems and thus to elevate the current image enhance...

Saif Mahmud, M Tanjid Hasan Tonmoy, Kumar Bhaumik Kishor, A K M Mahbubur Rahman et al.

Human Activity Recognition from body-worn sensor data poses an inherent challenge in capturing spatial and temporal dependencies of time-series signals. In this regard, the existing recurrent or convolutional or their hybrid models for activity recognition struggle to capture spatio-temporal context...

Md. Eusha Kadir, Pritom Saha Akash, Sadia Sharmin, Amin Ahsan Ali et al.

For the last two decades, more and more complex methods have been developed to identify human activities using various types of sensors, e.g., data from motion capture, accelerometer, and gyroscopes sensors. To date, most of the researches mainly focus on identifying simple human activities, e.g., w...

Md. Nazmul Haque, M Tanjid Hasan Tonmoy, Saif Mahmud, Amin Ahsan Ali et al.

Sensor data based Human Activity Recognition (HAR) has gained interest due to its application in practical field. With increasing number of approaches incorporating feature learning of sequential time-series sensor data, in particular the deep learning based ones has performed reasonably in uniform ...

Md. Mostafijur Rahman, Shanto Rahman, Rayhanur Rahman, B M Mainul Hossain et al.

Despite lots of effort being exerted in designing feature descriptors, it is still challenging to find generalized feature descriptors, with acceptable discrimination ability, which are able to capture prominent features in various image processing applications. To address this issue, we propose a c...

Pritom Saha Akash, Md. Eusha Kadir, Amin Ahsan Ali, Mohammad Shoyaib

This paper introduces a new splitting criterion called Inter-node Hellinger Distance (iHD) and a weighted version of it (iHDw) for constructing decision trees. iHD measures the distance between the parent and each of the child nodes in a split using Hellinger distance. We prove that this ensures the...

Md. Eusha Kadir, Pritom Saha Akash, Sadia Sharmin, Amin Ahsan Ali et al.

In k Nearest Neighbor (kNN) classifier, a query instance is classified based on the most frequent class of its nearest neighbors among the training instances. In imbalanced datasets, kNN becomes biased towards the majority instances of the training space. To solve this problem, we propose a method c...

Khalid Hussain, Shanto Rahman, Shah Mostafa Khaled, M. Abdullah‐Al‐Wadud et al.

Image enhancement processes an image to increase the visual information of that image. Image quality can be degraded for several reasons such as lack of operator expertise, quality of image capturing devices, etc. The process of enhancing images may produce different types of noises such as unnatura...

Sadia Sharmin, Amin Ahsan Ali, Muhammad Asif Hossain Khan, Mohammad Shoyaib

Feature selection and discretization have been considered to be an important research topic in the field of pattern recognition and data mining. However, addressing both these issues at a time is rarely discussed in the existing research. In this paper, these issues have been addressed by developing...