60 citations · 61 across the 5 of their papers we have counts for
5 papers
KonvLiNA: Integrating Kolmogorov-Arnold Network with Linear Nyström Attention for feature fusion in Crop Field Detection
Haruna Yunusa, Qin Shiyin, Adamu Lawan +1
Crop field detection is a critical component of precision agriculture, essential for optimizing resource allocation and enhancing agricultural productivity. This study introduces K…
VulCatch: Enhancing Binary Vulnerability Detection through CodeT5 Decompilation and KAN Advanced Feature Extraction
Abdulrahman Hamman Adama Chukkol, Senlin Luo, Kashif Sharif +2
Binary program vulnerability detection is critical for software security, yet existing deep learning approaches often rely on source code analysis, limiting their ability to detect…
iiANET: Inception Inspired Attention Hybrid Network for efficient Long-Range Dependency
Haruna Yunusa, Adamu Lawan, Abdulganiyu Abdu Yusuf
The recent emergence of hybrid models has introduced a transformative approach to computer vision, gradually moving beyond conventional convolutional neural networks and vision tra…
Exploring the Synergies of Hybrid CNNs and ViTs Architectures for Computer Vision: A survey
Haruna Yunusa, Shiyin Qin, Abdulrahman Hamman Adama Chukkol +3
The hybrid of Convolutional Neural Network (CNN) and Vision Transformers (ViT) architectures has emerged as a groundbreaking approach, pushing the boundaries of computer vision (CV…
SaRPFF: A Self-Attention with Register-based Pyramid Feature Fusion module for enhanced RLD detection
Yunusa Haruna, Shiyin Qin, Abdulrahman Hamman Adama Chukkol +2
Detecting objects across varying scales is still a challenge in computer vision, particularly in agricultural applications like Rice Leaf Disease (RLD) detection, where objects exh…