30 research outputs found
Hand detection and segmentation using smart path tracking fingers as features and expert system classifier
Nowadays, hand gesture recognition (HGR) is getting popular due to several applications such as remote based control using a hand, and security for access control. One of the major problems of HGR is the accuracy lacking hand detection and segmentation. In this paper, a new algorithm of hand detection will be presented, which works by tracking fingers smartly based on the planned path. The tracking operation is accomplished by assuming a point at the top middle of the image containing the object then this point slides few pixels down to be a reference point then branching into two slopes: left and right. On these slopes, fingers will be scanned to extract flip-numbers, which are considered as features to be classified accordingly by utilizing the expert system. Experiments were conducted using 100 images for 10-individual containing hand inside a cluttered background by using Dataset of Leap Motion and Microsoft Kinect hand acquisitions. The recorded accuracy is depended on the complexity of the Flip-Number setting, which is achieved 96%, 84% and 81% in case 6, 7 and 8 Flip_Numbers respectively, in which this result reflects a high level of finite accuracy in comparing with existing techniques
Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images
Diabetic Retinopathy (DR) is a major complication in human eyes among the diabetic patients. Early detection of the DR can save many patients from permanent blindness. Various artificial intelligent based systems have been proposed and they outperform human analysis in accurate detection of the DR. In most of the traditional deep learning models, the cross-entropy is used as a common loss function in a single stage end-to-end training method. However, it has been recently identified that this loss function has some limitations such as poor margin leading to false results, sensitive to noisy data and hyperparameter variations. To overcome these issues, supervised contrastive learning (SCL) has been introduced. In this study, SCL method, a two-stage training method with supervised contrastive loss function was proposed for the first time to the best of authors' knowledge to identify the DR and its severity stages from fundus images (FIs) using “APTOS 2019 Blindness Detection” dataset. “Messidor-2” dataset was also used to conduct experiments for further validating the model's performance. Contrast Limited Adaptive Histogram Equalization (CLAHE) was applied for enhancing the image quality and the pre-trained Xception CNN model was deployed as the encoder with transfer learning. To interpret the SCL of the model, t-SNE method was used to visualize the embedding space (unit hyper sphere) composed of 128 D space into a 2 D space. The proposed model achieved a test accuracy of 98.36%, and AUC score of 98.50% to identify the DR (Binary classification) and a test accuracy of 84.364%, and AUC score of 93.819% for five stages grading with the APTOS 2019 dataset. Other evaluation metrics (precision, recall, F1-score) were also determined with APTOS 2019 as well as with Messidor-2 for analyzing the performance of the proposed model. It was also concluded that the proposed method achieved better performance in detecting the DR compared to the conventional CNN without SCL and other state-of-the-art methods
2D Nanomaterial-Based Hybrid Structured (Au-WSe2-PtSe2-BP) Surface Plasmon Resonance (SPR) Sensor With Improved Performance
As a promising optical method used in a variety of applications surface plasmon resonance (SPR) sensors are employed over a wide range of boundaries. This research proposes a highly sensitive SPR based sensor with a novel hybrid structure using transition metal dichalcogenides (e.g. WSe 2 , PtSe 2 ) along with black phosphorene (BP) through comprehensive numerical study. To analyze and evaluate the performances of the proposed sensor, the widely used transfer matrix method (TMM) was used. The performances of the sensor were measured in terms of reflectivity, sensitivity, detection accuracy (DA), and figure of merit (FOM). The sensor structure was optimized by changing different structural parameters of the hybrid architecture to obtain better performances. The results revealed that insertion of PtSe 2 with WSe 2 and BP over a gold layer of the conventional structure improved the performance of the sensor and the maximum sensitivity of the sensor was measured as 200 deg/RIU with a FOM of 17.70 RIU −1 . As well, the light penetration through the optimized sensor is investigated using the finite element method (FEM) based software. With this kind of high sensing capabilities, it may be convinced that the proposed sensor can be applied in different fields of biosensing to detect liquid biological and biochemical samples or analytes
Numerical Study of Circularly Slotted Highly Sensitive Plasmonic Biosensor : A Novel Approach
Funding Information: This work was supported by the Deanship of the Scientific Research ( DSR ), King Abdulaziz University , Jeddah, under grant No. ( DF-773-135-1441 ). The authors, therefore, gratefully acknowledge DSR technical and financial support.Peer reviewe
Development of low profile unidirectional antenna for wireless local area network application
This thesis will review the project conducted the development of a low profile unidirectional antenna for WLAN applications, performed with frequency range 2.4-2.4835GHz. The Radial Waveguide Slot Array Antenna (RWSA) is investigated as a low profile, significant shape, lightly weight, simple but effective, easy to design and fabricate with reasonable cost efficient. Simulation and optimization of structure based on Zeland Fidelity - FDTD (Finite-Difference Time-Domain) with Full-3D EM Simulation for the radiation pattern, and return loss. The other part of this project deals with producing design relying on optimum simulation results. The developed antenna was tested in terms of return loss, gain and radiation pattern. Finally, integrated experimental trial had been compared with a monopole antenna on an Access point for WLAN. Measurements are conformed to results presented by the prototype simulatio
Terrestrial-To-Satellite Interference In The C band: Tractable Calculation Technique
This paper presents a research conducted on the interference mitigation between IMT-Advanced and Fixed
Satellite Services (FSS). It covers a deterministic
analysis for interference to noise ratio (I/N), adjacent
channel interference ratio (ACIR) and path loss propagation, in order to determine the separation distances
in the co-channel interference (CCI) and adjacent channel Interference (ACI) scenarios. An analytical model has been developed based on the deterministic analysis of the pr
opagation model. The IMT-Advanced parameters have been represented by Worldwide Interoperability for Microwave Access (WiMAX) 802.16e. The impact of different FSS channel bandwidths, guard band separations, antenna
heights and different deployment areas on co-existence feas
ibility are considered. The results obtained in terms of minimum required separation distance in three scenarios, co-channel, zero-guard band, and adjacent channel are analyzed
Interference Mitigation Technique Through Shielding and Antenna Discrimination
nterference mitigation between IMT-Advanced and Fixed Satellite Services (FSS) is
presented in this article. Toward this goal, an analytical model has been developed based on
the deterministic analysis of the propagation model. The IMT-Advanced system parameters
have been represented by Worldwide Interoperability for Microwave Access (WiMAX)
802.16e. The use of VSAT unit and different shielding materials is considered. The testing is
performed in the Anechoic Chamber as well as outdoor, and deployment is designed to fulfill
FSS signal receiving criteria. A strong positive correlation was found between path loss
parameters various terrains for different deployment areas. The Antenna discrimination has
been discussed alongside the shielding absorption coefficients of the suggested materials.
Then the antenna discrimination proposal is demonstrated with a high degree of capability to
reduce the harmful power interference from IMT-Advanced base station towards the FSS receiver