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Research

Towards automated weed detection through two-stage semantic segmentation of tobacco and weed pixels in aerial Imagery

S. Imran Moazzam, Umar S. Khan, Waqar S. Qureshi, Tahir Nawaz, Faraz Kunwar In precision farming, weed detection is required for precise weedicide application, and the detection of tobacco crops is necessary for pesticide application on tobacco leaves. Automated accurate detection of

Research

A new method for pixel classification for rice variety identification using spectral and time series data from Sentinel-2 satellite imagery

Usman Rauf, Waqar S. Qureshi, Hamid Jabbar, Ayesha Zeb, Alina Mirza, Eisa Alanazi, Umar S. Khan, Nasir Rashid In the agriculture sector food productivity, security, and sustainability, imposed challenges on farmers, regulatory bodies, and policymakers due to increasing demand and

Research Technology

Mango maturity classification instead of maturity index estimation: A new approach towards handheld NIR spectroscopy

Syed Sohaib Ali Shah, Ayesha Zeb, Waqar S. Qureshi, Aman Ullah Malik, Mohsin Tiwana, Kerry Walsh, Muhammad Amin, Waleed Alasmary, Eisa Alanazi Estimation of on-tree mango maturity is essential for the prediction of harvest time. Dry matter (DM) is a

Research

Improving classification performance of four class FNIRS-BCI using Mel Frequency Cepstral Coefficients (MFCC)

Muhammad Saad Bin Abdul Ghaffar, Umar S. Khan, J. Iqbal, Nasir Rashid, Amir Hamza, Waqar S. Qureshi, Mohsin I. Tiwana, U. Izhar Experimentation and analysis of Functional near-infrared spectroscopy (fNIRS) in Brain-Computer Interface (BCI) has increasingly been studied as a