Lamin L. Janneh

University of the Gambia, Guizhou University

Papers

Total Citations

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About

Lamin L. Janneh is a researcher advancing precision agriculture through deep learning and computer vision, with a focus on intelligent farm robotics. His work centers on the semantic segmentation of crops and weeds, addressing the challenge of distinguishing visually similar vegetation in complex field environments. Janneh’s major contributions include developing multi-level feature re-weighted fusion and hybrid feature selection methods for deep convolutional neural networks, which enhance the accuracy and robustness of robotic vision systems. His most-cited paper (2023, 34 citations) introduces an improved neural network architecture that effectively handles background interference, while a second highly cited work (2023, 13 citations) proposes a dual-branch deep network for robust feature representation. More recently, Janneh has extended his research to fruit crop management, designing a growth characteristics-based multi-class kiwifruit bud detection system with an overlap-partitioning algorithm for robotic thinning (2024, 6 citations). His work directly supports the development of automated weed control and precision thinning, reducing reliance on manual labor and chemical inputs. Janneh’s innovative algorithms are paving the way for faster, more accurate agricultural robots, making him a notable contributor to sustainable farming technology.