KNUST Research Atlas is currently in active Beta. Report bugs or suggest features to help us improve!
James Okae
This researcher has made significant contributions to the field of vision-based systems, advancing the integration of advanced computational techniques into real-world applications across diverse domains. Their work focuses on developing innovative methods for stereo matching and depth estimation, with a particular emphasis on leveraging mutual interaction principles for robust system performance. The researcher's research is characterized by its interdisciplinary approach, merging concepts from computer vision, robotics, and energy management to address challenges in smart grid optimization and image processing.
Advanced Vision and Imaging
Image Enhancement Techniques
Image Processing Techniques and Applications
Infrared Target Detection Methodologies
Smart Grid Energy Management
DMCNet: Toward Lightweight Volumetric Stereo Matching
Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion
Open AccessRobust Stereo Matching Using Discriminative Multilevel Features and Multimodal Bifurcated Cost Volume Network
Improved stereo matching framework with embedded multilevel attention
Concealed multiscale feature extraction network for automatic four-bar target detection in infrared imaging
Robust Scale-Aware Stereo Matching Network
Robust statistical approach to stereo disparity maps denoising and refinement
A novel depth estimation approach based on bidirectional matching for stereo vision systems
A Novel Method for Night-Time Single Image Dehazing
Open AccessOptimization of stereo vision depth estimation using edge-based disparity map
The Design and Realization of Smart Energy Management System based on Supply-Demand Coordination
Open AccessDepartment of Computer Engineering
Kwame Nkrumah University of Science and Technology