This research proposes a deep learning-oriented method for forecasting the co-morbidity of hypertension and diabetes utilizing Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) ...

By leveraging a vision foundation model called Depth Anything V2, the method can accurately segment crops across diverse environments—field, lab, and aerial—reducing both time and cost in agricultural ...

By integrating large-kernel convolutional blocks and a novel loss function, LKNet effectively addresses challenges such as ...

A research team has developed an advanced deep learning model, LKNet, to improve the accuracy of rice panicle counting in dense crop canopies.

By examining patterns in the text data and metadata linked to job adverts, The use of learning algorithms has grown in popularity in the detection of fraudulent job postings. For this, Research ...