油毡 发表于 2025-3-23 11:23:11
Retinal Vessel Classification Based on Maximization of Squared-Loss Mutual Information,etina and for the discovery of biomarkers associated with systemic diseases such as diabetes, hypertension, and cardiovascular disease. We introduce Squared-loss Mutual Information clustering (SMIC) for classifying arterioles and venules in retinal images for the first time (to the best of our knowlNAV 发表于 2025-3-23 15:22:01
Automated Spam Detection in Short Text Messages,er unwarranted material to users. This has led to a high influx of such . messages. In order to protect the interests of the user, several countermeasures have been deployed by telecommunication companies to hinder the volume of such spam. However, some volume of spam messages still manage to avoidfidelity 发表于 2025-3-23 18:10:50
http://reply.papertrans.cn/63/6204/620359/620359_13.pngMalfunction 发表于 2025-3-24 00:44:58
Reducing Inter-Scanner Variability in Multi-site fMRI Activations Using Correction Functions: A Prestatistical power of brain mapping studies made the researchers look at multi-center studies. But a major limitation in pooling data from multiple sites is the diversity in acquisition and analysis methods that effect the imaging results. This preliminary study aims at finding correcting functions tGULP 发表于 2025-3-24 02:49:52
Comparative Study of Preprocessing and Classification Methods in Character Recognition of Natural Ster Vision, more than the recognition of scanned documents due to several reasons. We propose a classification technique for classifying characters based on a pipeline of image processing operations and ensemble machine learning techniques. This pipeline tackles problems where Optical Character RecoALB 发表于 2025-3-24 07:28:53
http://reply.papertrans.cn/63/6204/620359/620359_16.pngsynovium 发表于 2025-3-24 14:18:51
http://reply.papertrans.cn/63/6204/620359/620359_17.png喃喃而言 发表于 2025-3-24 16:32:34
Retinal Blood Vessel Extraction and Optic Disc Removal Using Curvelet Transform and Morphological Oical operation. Since the curvelet transform represents the lines, the edges, the curvatures, the missing and the imprecise boundary details compactly, i.e., by smaller number of coefficients, they can be tuned suitably to enhance the image details. To remove the optic disc, the edge enhanced image无价值 发表于 2025-3-24 19:26:58
http://reply.papertrans.cn/63/6204/620359/620359_19.png圆木可阻碍 发表于 2025-3-25 01:34:51
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