Titlebook: Data Science and Communication; Proceedings of ICTDs Jo?o Manuel R. S. Tavares,Joel J. P. C. Rodrigues, Conference proceedings 2024 The Edi

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A Comparative Study of Disease Detection in Potato Plants Using Machine Learning and Deep Learning Me to potatoes. Early blight, late blight, and other diseases can spread in potato plants and display symptoms on leaves. If these epidemics are recognized early and preventative measures are followed, cultivators will not suffer significant financial losses. During the comparison analysis paper, the

Dawdle

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debble

Authentication Framework for?an?IoT Ecosystemity issues in IoT devices. The problems are in terms of device authentication and static key storage. We cannot implement any protocol directly in the IoT devices because of constrained devices and low computational power, which is a challenging task. We proposed the authentication framework based o

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IoT-Based Equinox Cooling Chamber Using Bolt IoT Module and Machine Learningmpanies use more advanced cooling chamber, but it is rare and expensive, and it does not have a way to check if the tablets got damaged. We plan to improve the chamber by incorporating machine learning and IoT-based concepts, as we all know, these days everything is moving online, so why should not

BAIL

galley

Fractal Features for Texture Analys?s dimension (FD). FD is a key feature that measures the level of roughness at multiple scales and is used to quantify the complexity of images. The standard method used to compute FD in greyscale images is the differential box counting (DBC) technique. However, this method has the limitations of over

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The Coming of Age of Electrocardiology extracted image features. The experiments were carried on ADNI1 dataset. The obtained result shows the accuracy of 96% for AD classification. Moreover, the sensitivity of the proposed method reveals that the model is less error prone in normal conditions.

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玉米棒子

Avram Bukhbinder,Paul E. Schulzfloods. Additionally, we monitor the highly susceptible area using the images clicked by the users before the onset of flood to detect blockages in the drainage and provide early information to the authorities to resolve the drainage blockage problems leading to urban flood.