Titlebook: Data Science and Applications; Proceedings of ICDSA Satyasai Jagannath Nanda,Rajendra Prasad Yadav,Muk Conference proceedings 2024 The Edit

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Complications in Cutaneous Surgery can be done by early diagnosis. However, due to the associated costs, clinical cataract detection and grading necessitate the expertise of qualified eye doctors, which may make everyone‘s early intervention difficult. The preset set of image features used in current analysis on automatic cataract d

conceal

Complications of Hallux Valgus Surgeryl electronic voting follows the fundamental laws that protects privacy and integrity of voters while preserving the openness and adaptability. In fact, fair election is not only essential to democratic governance but more importantly it can increase voters’ confidence and understanding of their role

植物茂盛

Management of Incision Complicationsough the analysis of medical imagery. The paper introduces an innovative framework for identifying infectious diseases using advanced convolutional neural network (CNN) models. The dataset encompasses diverse images of diseases like pneumonia, COVID-19, lung opacity, and MERS which have been sourced

招人嫉妒

Management of Incision Complications Sensors (IR) in addition to a NodeMCU ESP12E Module Controller has been used. The US is used to measure obstacle distance, while the two IR sensors measure the left and right wheel velocity. The ESP12E controller is connected to a L298N Driver Module for driving the two motors, and the motors are c

Bombast

https://doi.org/10.1007/978-3-319-53686-6containment. Based on the Environmental Census of India, a total of 42,799 wildfire sites were reported across the nation between March 1 and March 12, 2023. (FSI). Our initiative uses cutting-edge AI techniques to detect wildfires considerably earlier than conventional systems. We believe, however,

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ostensible

grounded

entreat

Michael T. Yen,Richard L. Andersony detection of the lesion and its treatment is necessary for malignant lesions. In this paper, we attempt to detect liver lesions using state-of-the-art single-stage object detection technology YOLOv8. On two distinct datasets, each of which contained 38 MR T1 fused image samples and 41 CT samples.

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