Detecting and recognizing faces from video images using multi-deep CNN based rank-level fusion

Ghosh, Manas; Sing, Jamuna Kanta

doi:10.1109/incacct61598.2024.10551246

2024 2nd International Conference on Advancement in Computation &Amp;amp; Computer Technologies (InCACCT) 2024

DOI: 10.1109/incacct61598.2024.10551246

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Detecting and recognizing faces from video images using multi-deep CNN based rank-level fusion

Manas Ghosh,

Jamuna Kanta Sing

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Forecasting the Right Crop Nutrients for Specific Crops Based on Collected Data Using an Artificial Neural Network (ANN)

Amertet,

Gebresenbet

2024

MAKE

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In farming technologies, it is difficult to properly provide the accurate crop nutrients for respective crops. For this reason, farmers are experiencing enormous problems. Although various types of machine learning (deep learning and convolutional neural networks) have been used to identify crop diseases, as has crop classification-based image processing, they have failed to forecast accurate crop nutrients for various crops, as crop nutrients are numerical instead of visual. Neural networks represent an opportunity for the precision agriculture sector to more accurately forecast crop nutrition. Recent technological advancements in neural networks have begun to provide greater precision, with an array of opportunities in pattern recognition. Neural networks represent an opportunity to effectively solve numerical data problems. The aim of the current study is to estimate the right crop nutrients for the right crops based on the data collected using an artificial neural network. The crop data were collected from the MNIST dataset. To forecast the precise nutrients for the crops, ANN models were developed. The entire system was simulated in a MATLAB environment. The obtained results for forecasting accurate nutrients were 99.997%, 99.996%, and 99.997% for validation, training, and testing, respectively. Therefore, the proposed algorithm is suitable for forecasting accurate crop nutrients for the crops.

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Forecasting the Right Crop Nutrients for Specific Crops Based on Collected Data Using an Artificial Neural Network (ANN)

Amertet,

Gebresenbet

2024

MAKE

View full text Add to dashboard Cite

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Detecting and recognizing faces from video images using multi-deep CNN based rank-level fusion

Cited by 1 publication

References 24 publications

Forecasting the Right Crop Nutrients for Specific Crops Based on Collected Data Using an Artificial Neural Network (ANN)

Forecasting the Right Crop Nutrients for Specific Crops Based on Collected Data Using an Artificial Neural Network (ANN)

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