0000000000398478
AUTHOR
Muhammad Ismail
A Simple and Efficient Deep Learning-Based Framework for Automatic Fruit Recognition
Accurate detection and recognition of various kinds of fruits and vegetables by using the artificial intelligence (AI) approach always remain a challenging task due to similarity between various types of fruits and challenging environments such as lighting and background variations. Therefore, developing and exploring an expert system for automatic fruits’ recognition is getting more and more important after many successful approaches; however, this technology is still far from being mature. The deep learning-based models have emerged as state-of-the-art techniques for image segmentation and classification and have a lot of promise in challenging domains such as agriculture, where they can …
Evaluation of Deep Learning and Conventional Approaches for Image Recaptured Detection in Multimedia Forensics
Image recaptured from a high-resolution LED screen or a good quality printer is difficult to distinguish from its original counterpart. The forensic community paid less attention to this type of forgery than to other image alterations such as splicing, copy-move, removal, or image retouching. It is significant to develop secure and automatic techniques to distinguish real and recaptured images without prior knowledge. Image manipulation traces can be hidden using recaptured images. For this reason, being able to detect recapture images becomes a hot research topic for a forensic analyst. The attacker can recapture the manipulated images to fool image forensic system. As far as we know, ther…
Removal of Brilliant Green Dye from Water Using Ficus benghalensis Tree Leaves as an Efficient Biosorbent
The presence of dyes in water stream is a major environmental problem that affects aquatic and human life negatively. Therefore, it is essential to remove dye from wastewater before its discharge into the water bodies. In this study, Banyan (Ficus benghalensis, F. benghalensis) tree leaves, a low-cost biosorbent, were used to remove brilliant green (BG), a cationic dye, from an aqueous solution. Batch model experiments were carried out by varying operational parameters, such as initial concentration of dye solution, contact time, adsorbent dose, and pH of the solution, to obtain optimum conditions for removing BG dye. Under optimum conditions, maximum percent removal of 97.3% and adsorption…
Face Mask Detection Using Deep Convolutional Neural Network and MobileNetV2-Based Transfer Learning
The rapid spreading of Coronavirus disease 2019 (COVID-19) is a major health risk that the whole world is facing for the last two years. One of the main causes of the fast spreading of this virus is the direct contact of people with each other. There are many precautionary measures to reduce the spread of this virus; however, the major one is wearing face masks in public places. Detection of face masks in public places is a real challenge that needs to be addressed to reduce the risk of spreading the virus. To address these challenges, an automated system for face mask detection using deep learning (DL) algorithms has been proposed to control the spreading of this infectious disease effecti…