Early recognition of maize leaf disorders and applying precautionary measures on time may help to increase the yield and quality. This study introduces an architecture for the recognition and categorization of maize leaf diseases based on the deep Inception-v3 and maximum value-based color features. The core steps of the designed framework include data acquisition, feature extraction, fusion, and classification. The maize leaf image dataset is utilized, which is publicly available on Kaggle, comprising four classes. The deep learning features are collected by applying the transfer learning approach to the pre-trained Inception-v3 model. In addition to the deep features, maximum value-based c... More >

Breast Cancer (BC) is still one of the most significant, life-threatening, and prevalent diseases that affects women all around the globe. The early recognition and strategies of effective treatment measures improve the rate of survival among patients significantly, contributing to a critical research area in medical science. This review presents a comprehensive review of recent trends and advancements in the recognition of BC recognition, diagnosis, and treatment. It covers multiple imaging modalities, including Magnetic Resonance Imaging (MRI), ultrasound, mammography, and histopathology, along with various approaches of Machine Learning (ML) and Deep Learning (DL) that enhance the efficie... More >