Assessment of inhibitory potentiality of natural compounds against worrisome rice blast fungus.

Rice blast, a severe fungal disease, is a substantial threat to global food security, particularly in rice-oriented areas. The fungus is increasingly resistant and fast developing in nature. However, chemical fungicides are not only detrimental to the environment but eventually also lose their efficiency.

Autism spectrum disorder detection using facial images: A performance comparison of pretrained convolutional neural networks.

Autism spectrum disorder (ASD) is a complex psychological syndrome characterized by persistent difficulties in social interaction, restricted behaviours, speech, and nonverbal communication. The impacts of this disorder and the severity of symptoms vary from person to person. In most cases, symptoms of ASD appear at the age of 2 to 5 and continue throughout adolescence and into adulthood.

Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things.

Introduction: Particularly within the Internet of Medical Things (IoMT) context, skin lesion analysis is critical for precise diagnosis. To improve the accuracy and efficiency of skin lesion analysis, CAD systems play a crucial role. To segment and classify skin lesions from dermoscopy images, this study focuses on using hybrid deep learning techniques.

A Neural Network-Inspired Approach for Improved and True Movie Recommendations.

In the last decade, sentiment analysis, opinion mining, and subjectivity of microblogs in social media have attracted a great deal of attention of researchers. Movie recommendation systems are the tools, which provide valuable services to the users. The data available online are growing gradually because the online activities of users or viewers are increasing day by day.