Browsing by Author "Zahid Hasan"

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    Open Access
    A Comparative Study of Machine Learning Techniques for Autism Spectrum Disorder (ASD) Detection
    (North South University, 2022) Zahid Hasan; Towsif Muhtadi Khan; Dr. Atiqur Rahman; 1911509042; 1911576042
    Autism Spectrum Disorder (ASD) is a developmental impairment caused by brain differences. ASD patients may have a recognized difference, such as a genetic disease [1]. Autism can be diagnosed at any age and is referred to as a "behavioral disorder" since symptoms often develop within the first two years of life [1]. In this study, we have implemented different classifier algorithms such as Decision Tree Classifier, Logistic Regression, and Multi-layer Perceptron classifier (MLP Classifier) for detecting ASD in three types of people - adults, adolescents, and children. The proposed techniques are evaluated on publicly available three different non-clinically ASD datasets [2]. After applying various machine learning techniques and handling missing values, results strongly suggest that ANN-based prediction models work better on all these datasets with higher accuracy of 98.58%, 98.30%, and 95.24% for Autistic Spectrum Disorder Screening Data for Adults, Children, and Adolescents, respectively.
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    Open Access
    A Real Time Pothole and Speed Breaker Detection Using Deep Learning
    (North-south University, 2019-04-30) Zahid Hasan; Tasmia Rahman Shahidi; Samsoon Nahar Shampa; Dr. Shahnewaz Siddique; 1510846042; 1521367642; 1511148042
    The road accident rate in Bangladesh is increasing day by day due to various reasons. One of these reasons are poor road conditions. Unwanted potholes, missing pitches, improper speed breakers, unfinished manhole covers and slabs transform many roads into obstacles courses thus greatly increasing the probability of serious accidents. However, the arrival of new assistive driving technologies hold much promise in making the roads the safer and avoid serious accidents and damages. The main goal of our project is to create real-time assistive technologies to detect potholes and speed breakers for on-road drivers in general but especially for bikers and cyclists. Our system will provide drivers with advance notification about upcoming potholes and speed breakers and thus assist in avoiding unwanted accidents. Our system will provide drivers sufficient time to react to and avoid these impending road hazards