Deep learning technique for grape leaf disease classification via deep high attention stage-by-stage forward Taylor network

Hybrid fusion of E-nose and computer vision using optimized deep learning and machine learning for robust plant leaf recognition

Pouya Bohlol, Mohammad Hasan Sabet Dizavandi, Syed Saeid Mohtasebi, Mahmoud Omid

Abstract The fusion multi-sensory system with optimized deep learning and machine learning algorithms appeared to synergize difficult paradigms in precision agriculture and boost recognition of various plant species. In this study, an electronic nose (E-nose) system with eight MO…Read more

A hybrid explainable deep learning framework for blood cancer classification using CNN-based feature embeddings and random forest decision models

Zulfikar Ali Ansari, Hemlata Pant, Nayancy, M. N. V. Kiranbabu, Sanjeet Kumar

The precision and early detection of subtypes of acute lymphoblastic leukaemia (ALL) in peripheral blood smear images are crucial for efficient clinical practice. Traditional deep learning methods tend to be challenging in terms of model interpretation and are often reliant on la…Read more

Deep learning-based classification of benign anorectal lesions on endoanal ultrasound: a proof-of-concept study

Maria João Almeida, Miguel Mascarenhas, Miguel Martins, F Mendes, Joana Mota, Pedro Cardoso, et al.

Benign anorectal conditions—including fissures, lacerations, and fistulas—are common and often require precise imaging for adequate diagnosis and surgical planning. Endoanal ultrasonography (EAUS) offers excellent visualization of the sphincter complex but remains underused due t…Read more

Prediction of the axial capacity of various polygon-type section concrete-filled steel (CFST) columns utilising deep neural network and machine learning regressor

Yue Chen, Haytham F. Isleem, Bagas R. Subchan, Mohammad Khishe

MSE-YOLOv8n: a cotton leaf disease detection model for complex backgrounds and small targets

Kaisi Xue, W. Zhang, Ziwei Gan, Chengkun Zhang

As one of China’s pivotal cash crops, cotton’s leaf health directly impacts the textile industry and agricultural economic growth, with leaf diseases emerging as a critical constraint on cotton yield. Traditional manual identification of cotton leaf diseases, plagued by high subj…Read more

An explainable AI framework integrating machine and deep learning models for multi-species DNA functional group classification

Pratik Chakraborty, P. B. Shanthi

Abstract DNA functional group classification across species plays a crucial role in understanding genetic diversity, evolutionary relationships and biological function. The increasing availability of genomic data has led to the use of machine learning and deep learning methods fo…Read more