Several HISTOGRAM equalization methods for enhancing the color images of Rosa Damascena flowers and some THRESHOLDING methods for segmentation of the flowers were examined. Images were taken outdoors at different times of day and light conditions. A factorial experiment in the form of a Completely Randomized Design with two factors of HISTOGRAM equalization method at 8 levels and THRESHOLDING method at 15 levels, was implemented. HISTOGRAM equalization methods included: CHE, BBHE, BHEPL-D, DQHEPL, DSIHE, RMSHE, RSIHE, and no HISTOGRAM equalization (NHE) as the control. THRESHOLDING method levels were: Huang, Intermodes, Isodata, Li, maximum entropy, mean, minimum, moments, Otsu, percentile, Renyi‟ s entropy, Shanbhag, Yen, constant, and global basic THRESHOLDING method. The effect of these factors on the properties of the segmented images such as the Percentage of Incorrectly Segmented Area (PISA), Percentage of Overlapping Area (POA), Percentage of Undetected Area (PUA), and Percentage of Detected Flowers (PDF) was investigated. Results of HISTOGRAM equalization analysis showed that DQHEPL and NHE have the statistically significant lowest PUA (11. 13% and 8. 32%, respectively), highest POA (89. 35% and 92. 07%, respectively), and highest PDF (61. 88% and 64. 94%, respectively). THRESHOLDING methods had a significant effect on PISA, PUA, POA, and PDF. The highest PDF belonged to constant, minimum, and Intermodes (75. 07%, 73. 08% and 74. 30%, respectively) They also had the lowest PISA (0. 35%, 1. 29%, and 1. 85%, respectively) and PUA (33. 72%, 23. 09%, and 15. 56%, respectively). These methods had the highest POA (80. 73%, 76. 70%, and 84. 67%, respectively). Hence, they are suitable methods for segmentation of Rosa Damascena flowers in color images.

In order to detect targets upon sea surface or near it, marine radars should be capable of distinguishing signals of target reflections from the sea clutter. Our proposed method in this paper relates to detection of dissimilar marine targets in an inhomogeneous environment with clutter and non-stationary noises, and is based on adaptive THRESHOLDING determination methods. The variance and the mean values of the noise level have been estimated in this paper, based on non-stationary, statistical methods and THRESHOLDING has been carried out using the suggested two-pole recursive filter. Making the rate of false alarm constant, the concerned threshold resolves the hypothesis of existence or absence of the target signal. Performance of the mentioned algorithm has been compared with the well-known conventional method as CA-CFAR in terms of decreasing the losses and increasing calculation speed. The algorithm provided for detection of signal has been implemented as a part of signal-processing algorithms of some practical marine radar. The results obtained from the algorithm performance in a real environment indicate appropriate workability of this method in heterogeneous environment and non-stationary interference.

Purpose: To compare the results of the new strategy Swedish Interactive THRESHOLDING Algorithm (SITA) Faster to the results of SITA Standard in patients with glaucoma. Methods: This was a cross-sectional study of 49 patients with glaucoma and previous experience with standard automated perimetry. Two consecutive tests were performed in random order, one with SITA Standard and another one with SITA Faster, in the studied eye of each patient. Comparisons were made for test time, mean deviation (MD), visual field index (VFI), and number of depressed points in pattern deviation map and total deviation map for every level of significance. Results: The average test time was 56% shorter with SITA Faster (P < 0. 001). The intraclass correlation coefficient (ICC) for MD and VFI showed excellent agreement between both strategies, ICC = 0. 98 (95% confidence interval [CI]: 0. 96, 0. 99) and ICC = 0. 97 (95% CI: 0. 95, 0. 99), respectively. For the number of depressed points in total deviation map and pattern deviation map, ICC demonstrated good agreement with values between 0. 8 and 0. 95. Conclusions: Our study shows that SITA Faster is a shorter test with strong agreement with SITA Standard parameters. These results suggest that SITA Faster could replace SITA Standard for glaucoma diagnosis.

Out-of-domain intent detection in natural language understanding systems faces significant challenges from suboptimal threshold selection and signal degradation through inappropriate normalization techniques. This paper presents an adaptive ensemble THRESHOLDING framework that substantially extends our previous conference work by addressing fundamental limitations in existing variational autoencoder-based detection methods. Our approach combines reconstruction loss from variational autoencoders with classifier confidence scores to create a unified detection signal that captures both semantic deviation and prediction uncertainty. The framework incorporates a novel smart scaling strategy that preserves natural separation ratios between in-domain and out-of-domain samples, preventing the signal destruction caused by standard normalization approaches. Through systematic parameter optimization using grid search techniques, the method adaptively determines optimal ensemble weights and threshold selection strategies tailored to specific dataset characteristics. We evaluate our framework across multiple datasets with varying semantic complexity and domain structures, demonstrating consistent performance improvements over baseline variational autoencoder approaches and recent state-of-the-art methods. Compared to our previous VAE-based approach, the framework demonstrates an average performance gain of 3.15 percentage points across all evaluation metrics. Our analysis reveals that ensemble scaling strategy significantly impacts detection performance, with proper signal preservation being more critical than sophisticated threshold selection methods. This work provides a principled approach to adaptive ensemble learning for out-of-domain detection, offering a robust solution that generalizes effectively across diverse datasets and linguistic contexts including low-resource languages like Persian.

This paper addresses the problem of speech enhancement in wavelet domain. After decomposition of noisy signal into wavelet sub-bands, an adaptive THRESHOLDING process is applied on wavelet coefficients. In the proposed technique, small threshold value and hard thrsholding function are used in sub-bands with high speech energy; vice versa, in sub-bands with low speech energy, large threshold value and soft THRESHOLDING function are employed. For other sub-bands (between above two extreme cases for speech energy), we use an adaptive THRESHOLDING function that is actually between soft- and hard-THRESHOLDING functions. The threshold value and THRESHOLDING function are determined by a parameter related to the ratio of speech and noise powers in each sub-band. Our extensive experiments show the superiority of proposed method in removing the background noise and reduction of speech distortion. It was also shown that both wavelet tree structure and wavelet type affect on the performance of speech de-noising system.

Coast is a unique environment in which atmosphere, hydrosphere and lithosphere contact each other. Coastline is one of the most important linear features on the earth’s surface, which display a dynamic nature. Coastal zone, and its environmental management requires the information about coastlines and their changes. This paper examines the current methods of coastline change detection using satellite images. Based on the advantages and drawbacks of the methods, a new procedure has been developed. The proposed procedure is based on a combination of HISTOGRAM THRESHOLDING and band ratio techniques. The study area of the project is Urmia Lake; the 20th. largest, and the second hyper saline lake in the world. In order to assess the accuracy of the results, they have been compared with ground truth observations. The accuracy of the extracted coastline has been estimated as 1.3 pixels (pixel size=30 m). Based on this investigation, the area of the lake has been decreased approximately 1040 square kilometers from August 1998 to August 2001. This result has been verified through TOPEX/Posidon satellite information that indicates a height variation of three meters.