Titlebook: Advances in Data-Driven Computing and Intelligent Systems; Selected Papers from Swagatam Das,Snehanshu Saha,Jagdish C. Bansal Conference pr

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Geology of the Greenbrier Valley,th less use of resources. Using a machine learning technique, research is attempting to predict soil characteristics. Sand, pH value, Soil organic Carbon, Calcium, and Phosphorus are the primary characteristics of soil forecasts. These characteristics have a significant influence on crop yields. Six

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Greg A. Brick,E. Calvin Alexander Jr.low more precautions for food consumption. The conventional technique of food safety is not capable of ensuring food safety very precisely and has many limitations so the food business operators are facing economic losses. To resolve these limitations, the researchers and scientists developed AI-bas

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Daniel H. Doctor,E. Calvin Alexander Jr.staple crops, providing essential nutrition to millions worldwide. However, many tomato and potato leaf diseases can seriously reduce food productivity and yields. We are proposing a hybrid deep learning model that combines optimized CNN (OCNN) and optimized LSTM (OLSTM). The weight values of LSTM a

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Jacqueline Loss,José Manuel Prietonces for multimedia, the field of image forensic has also made significant progress in recent years with the development of effective and more advanced image tampering detection methods. Furthermore, there has been continuous development in the image tampering methods along with the techniques used

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The Hare and the Turtle: The Black f the plate. A camera captures Chladni patterns for training, classification, and prediction of respective frequencies using deep learning algorithm. The Chladni patterns formed, depend on the material properties, geometry, thickness, and the vibration frequency. The experimental setup consists of a

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Jacqueline Loss,José Manuel Prietomensions of an image while preserving the finer texture characteristics is image super resolution. This paper proposes a new model to deal with the reconstruction time and artifacts that GAN-based deep learning models face. To increase the speed, FASRGAN aims at reducing the complexity of generators

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The Hare and the Turtle: The Black an Premier League (IPL). Utilizing machine learning models (linear SVM and logistic regression), we effectively categorized sentiments into negative, neutral, and positive classes, attaining impressive overall accuracy of 96.8% and 97.1%, respectively. The geospatial analysis led to map sentiment ac