Ahamed Shafeeq B M

Dept. of Computer Science and Engineering, Manipal Institute of Technology, Manipal University, Manipal, Karnataka State. Pin 576104
India

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A unified framework with U-Net + + and CNN-RNN-BiGRU architectures for automated weed detection in precision agriculture using AI
Patel, V. K., Abhishek, K. & Shafeeq, B. M. A., 12-2026, In: Discover Artificial Intelligence. 6, 1, 144.
Research output: Contribution to journal › Article › peer-review

Open Access
SentXFormer: a transformer-enhanced hybrid deep learning framework for cross-domain sentiment analysis of customer reviews
Kumar, A., Abhishek, K. & Shafeeq B M, A., 12-2026, In: Scientific Reports. 16, 1, 3528.
Research output: Contribution to journal › Article › peer-review

Open Access
A hybrid deep learning and differential evolution approach for accurate fake news detection
Singh, S. P., Kumar, N., Kumar, G. & Ahamed, A. S., 12-2025, In: Systems and Soft Computing. 7, 200365.
Research output: Contribution to journal › Article › peer-review

Open Access
1 Link opens in a new tab Citation (Scopus)
A twin CNN-based framework for optimized rice leaf disease classification with feature fusion
Pai, P., Amutha, S., Basthikodi, M., Ahamed Shafeeq, B. M., Chaitra, K. M. & Gurpur, A. P., 12-2025, In: Journal of Big Data. 12, 1, 89.
Research output: Contribution to journal › Article › peer-review

Open Access
23 Link opens in a new tab Citations (Scopus)
Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction
Ali, N. S. M. & Shafeeq, B. M., 2025, 3rd International Conference on Business Analytics for Technology and Security, ICBATS 2025. Institute of Electrical and Electronics Engineers Inc., (3rd International Conference on Business Analytics for Technology and Security, ICBATS 2025).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ahamed Shafeeq B M

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Collaborations and top research areas from the last five years

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A unified framework with U-Net + + and CNN-RNN-BiGRU architectures for automated weed detection in precision agriculture using AI

SentXFormer: a transformer-enhanced hybrid deep learning framework for cross-domain sentiment analysis of customer reviews

A hybrid deep learning and differential evolution approach for accurate fake news detection

A twin CNN-based framework for optimized rice leaf disease classification with feature fusion

Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction

Ahamed Shafeeq B M

Personal profile

Fingerprint

Collaborations and top research areas from the last five years

Research output

A unified framework with U-Net + + and CNN-RNN-BiGRU architectures for automated weed detection in precision agriculture using AI

SentXFormer: a transformer-enhanced hybrid deep learning framework for cross-domain sentiment analysis of customer reviews

A hybrid deep learning and differential evolution approach for accurate fake news detection

A twin CNN-based framework for optimized rice leaf disease classification with feature fusion

Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction