WIRELESS SENSOR NETWORKS AND APPLICATIONS
Published In: 4TH INTERNATIONAL E-CONFERENCE ON ENGINEERING, TECHNOLOGY AND MANAGEMENT
Author(s): ELIZA BAJRAMI , USTIJANA RECHKOSKA- SHIKOSKA
Abstract: Wireless sensor networks (WSNs) had grown in recent years and have a significant potential in different applications including health, environment, military, etc. The successful development and design of WSN is still a challenging task. In current real-world WSN deployments, different programming approaches have been proposed. Several aspects of Wireless sensor networks applications are presented, and an algorithm for forecast of predicting the weather in the next couple of days, using signal processing techniques is presented in this work. An evaluation is made by performing certain simulations; discussion, conclusion and future work goals are given, including the idea of an expansion of this research in WSNs applications in healthcare.
- Publication Date: 24-Jan-2021
- DOI: 10.15224/978-1-63248-191-7-09
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GLAUCOMA SCREENING USING SIMPLE FUSION FEATURES
Published In: 4TH INTERNATIONAL E-CONFERENCE ON ENGINEERING, TECHNOLOGY AND MANAGEMENT
Author(s): PANAREE CHAIPAYOM , SOMYING THAINIMIT
Abstract: Glaucoma is the second most common cause of blindness. It is caused by high intraocular pressure within the eyes, resulting in an injury to the optic nerve. Currently, there is no cure for glaucoma. However, early detection and treatment can prevent disease progression. Thus, the use of automatic glaucoma screening system can help workload of healthcare professionals in early detection and also solve cost issues. This study proposes a method for identifying glaucoma from fundus images by using a fusion three features to find glaucoma’s significant by using wavelet decomposition and texture such as Discrete Wavelet Transform (DWT), Principal Components Analysis (PCA), and Local Binary Patterns (LBP). Support vector machine (SVM) is used to classify the glaucoma condition. The experimental results yield high accuracy at 95% by using tenfold cross-validation with HRF Database and using fusion three feature as DWT, PCA, and LBP.
- Publication Date: 24-Jan-2021
- DOI: 10.15224/978-1-63248-191-7-10
- Views: 0
- Downloads: 0