Insects comprise millions of species, many experiencing severe population declines under environmental and habitat changes. High-throughput approaches are crucial for accelerating our understanding of insect diversity, with DNA barcoding and high-res... read more
In this study, we propose a new hybrid deep learning architecture combining Vision Transformers (ViT) with Convolutional Attention Blocks (CAB), specifically designed for automated weed detection in precision agriculture. We introduce a novel coupled... read more
This study presents Temporal Convolutional Network-Bidirectional Gated Recurrent Unit-Multi Head Attention (TCN-BiGRU-MHA) hybrid deep learning model optimized with the Enhanced Dhole Optimization Algorithm (EDOA) for wind power estimation using real... read more
Grain number estimation plays a crucial role in agriculture, serving as a key indicator for crop yield and quality assessment. With advances in computer vision, automatic grain detection has become a significant research area, where deep learning met... read more
The use of artificial intelligence (AI) in high-rise building rectification is emerging as an essential way to address structural issues. This study explores how AI technologies are used in lifting, grouting, and reinforcement to enhance safety, effi... read more
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