Weed removal is crucial in improving agricultural productivity, but current image processing algorithms struggle to accurately differentiate between weeds and crops, leading to suboptimal outcomes. The selection of appropriate ...

The rapid advancements in generative artificial intelligence have led to growing demand for accessible and open-source tools that enable users to create and edit images using AI models. However, the high computational ...

"his study presents the development of a novel algorithm, QAPNet(Quantization Attention Pruning Network), and its comprehensive evaluation, demonstrating its superior performance compared to traditional deep learning ...

Outliers, which were previously viewed as noisy information in statistics, have become a significant issue under extensive study across various academic disciplines and professional domains. In this study, we examined how ...

"Nowadays, facial recognition technology has improved significantly, greatly enhancing security, personalized customer experiences, and reliable biometric verification. But the emergence of deepfake technology, where AI ...

Advances in breast cancer screening programs have received significant attention due to their potential to improve early detection, accuracy, and efficiency in diagnosing breast disease. Timely diagnosis and accurate staging ...

In the recent times, intensifying struggles for sustenance and education, have sharply escalated competitive tensions among individuals. This heightened competition has left many students especially the adolescents in ...

With companies incorporating agile software practices and with the increase in the number of developers collaborating on a given product, it becomes important to automate the development pipeline (build, test and deploy). ...

Deep neural networks have achieved revolutionary results in several domains; nevertheless, they require extensive computational resources and memory footprint. Research has been conducted in the field of knowledge distillation, ...

Brain tumours are the main reason for 85% - 90% of all the primary CNS (central nervous system) tumours. Nearly 70% to 75% of Brain Tumours are undetected in early stages. The implemented model used Deep CNN and U-Net ...