Titlebook: Computer Vision and Image Processing; 6th International Co Balasubramanian Raman,Subrahmanyam Murala,Puneet G Conference proceedings 2022 T

被告

,Leaf Segmentation and?Counting for?Phenotyping of?Rosette Plants Using Xception-style U-Net and?Watth the dice coefficient of 0.9685. Xception-style U-Net, along with the watershed algorithm, achieves an average difference in leaf count (DiC) of 0.26 and absolute difference in leaf count (.) of 1.93, better than existing methods in the literature.

擺動

,Fast and?Secure Video Encryption Using Divide-and-Conquer and?Logistic Tent Infinite Collapse Chaotls are arranged into frames and pixels are further substituted at frame level with another chaotic sequence generated by LT-ICM. Experimental results establish that our proposed method is efficient in terms of encryption time, correlation coefficients and entropy values compared to some of the exist

LAIR

,Detection of?Cataract from?Fundus Images Using Deep Transfer Learning,l parameters evenly. Its scaling approach consistently scales network breadth, depth, and resolution with a set of predefined scaling coefficients. Experiments have been conducted on the publicly available ODIR dataset (Ocular Disease Intelligent Recognition) and the proposed method is validated usi

RALES

LAY

https://doi.org/10.1007/978-1-4302-3052-61e?2, 1e?3 and 1e?4 and sgdm, adam, rmsprop as optimizers. Further the same networks are experimented using classifiers support vector machine (SVM), k nearest neighbor (KNN) and decision tree (DT) for varied learning rates and optimizers. Inception-v4 network has observed an highest overall accurac

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歹徒

首創(chuàng)精神

BRIDE

David Hows,Peter Membrey,Tim Hawkins-class classification problem, the EfficientNet-B7 model has achieved the highest classification accuracy of 90.90%. With such a high rate of success, the EfficientNet-B7 model may be a useful method for pathologists in determining the stage of prostate cancer.

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