Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

Plant diseases are a severe cause of crop losses in the agriculture globally. Detection of
diseases in plants is difficult and challenging due to the lack of expert knowledge. Deep …

Emotion identification based on multimodal data (eg, audio, video, text, etc.) is one of the
most demanding and important research fields, with various uses. In this context, this …

Short-term rainfall forecasting plays an important role in hydrologic modeling and water
resource management problems such as flood warning and real time control of urban …

Conventional weed management approaches are inefficient and non-suitable for integration
with smart agricultural machinery. Automatic identification and classification of weeds can …

Within last decade, the investing habits of people is rapidly increasing towards stock market.
The nonlinearity and high volatility of stock prices have made it challenging to predict stock …

Background Currently, there is an urgent need for efficient tools to assess the diagnosis of
COVID-19 patients. In this paper, we present feasible solutions for detecting and labeling …

Identification of brain tumors at an early stage is crucial in cancer diagnosis, as a timely
diagnosis can increase the chances of survival. Considering the challenges of tumor …

Background Discharge medical notes written by physicians contain important information
about the health condition of patients. Many deep learning algorithms have been …