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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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The evaluation of contentoriented XML document retrieval: a case study of official letter / Hayati Abd Rahman
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Data depublication using : Hashing algorithm / Naimah Nayan
Published 2019“…The recommendation for future work is to evaluate various type of data and different type of hashing algorithm.…”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images
Published 2018“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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Evaluation method of rationality of urban landscape facility design based on neural network
Published 2025“…Therefore, this study formulates a scientific and reasonable evaluation index system for the rationality of urban landscape facility design and uses a neural network to carry out intelligent evaluation, in order to obtain optimal evaluation outcomes. …”
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Blogs Search Engine Adopting RSS Syndication Using Fuzzy Logic
Published 2012“…The blogs search engine consists of three main phases which are crawling using RSS feeds algorithm, indexing weblogs algorithm and searching technique with Fuzzy logic. …”
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan
Published 2022“…The performance of the proposed routing algorithm has been evaluated through simulations of well-known software MATLAB. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia
Published 2021“…Seven satellite images and indices combinations include Landsat 8 (C1), Sentinel-2 (C2), Landsat 8+Sentinel-2 (C3), Landsat 8+Indices (C4), Sentinel-2+Indices (C5), Landsat 8+Sentinel-2+Indices (C6), Normalized Difference Vegetation Index (NDVI)+Normalized Difference Water Index (NDWI)+Enhanced Vegetation Index (EVI)+Elevation (C7) were developed to evaluate the best combination for land use mapping in the Johor River Basin (JRB), Malaysia. …”
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