output
20062026
most citedLess is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease Classification

195 citations

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15 papers · 1 filter

cs.LG2026★ 5 cited

SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal

Rafsan Jany, Md. Hamjajul Ashmafee, Iqram Hussain +1

Classification of sleep stages is one of the most important diagnostic approaches for a variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful t…

cs.LG2025

Risk Prediction of Cardiovascular Disease for Diabetic Patients with Machine Learning and Deep Learning Techniques

Esha Chowdhury

Accurate prediction of cardiovascular disease (CVD) risk is crucial for healthcare institutions. This study addresses the growing prevalence of diabetes and its strong link to hear…

cs.LG2025★ 1 cited

Attention-Enhanced LSTM Modeling for Improved Temperature and Rainfall Forecasting in Bangladesh

Usman Gani Joy, Shahadat kabir, Tasnim Niger

Accurate climate forecasting is vital for Bangladesh, a region highly susceptible to climate change impacts on temperature and rainfall. Existing models often struggle to capture l…

cs.LG2025

AdeptHEQ-FL: Adaptive Homomorphic Encryption for Federated Learning of Hybrid Classical-Quantum Models with Dynamic Layer Sparing

Md Abrar Jahin, Taufikur Rahman Fuad, M. F. Mridha +2

Federated Learning (FL) faces inherent challenges in balancing model performance, privacy preservation, and communication efficiency, especially in non-IID decentralized environmen…

cs.LG2023★ 6 cited

An Explainable Machine Learning Framework for the Accurate Diagnosis of Ovarian Cancer

Asif Newaz, Abdullah Taharat, Md Sakibul Islam +1

Ovarian cancer (OC) is one of the most prevalent types of cancer in women. Early and accurate diagnosis is crucial for the survival of the patients. However, the majority of women…

cs.LG2022★ 2 cited

AutoCl : A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance

Fuad Ahmed, Rubayea Ferdows, Md Rafiqul Islam +1

Nowadays, deep learning (DL) models being increasingly applied to various fields, people without technical expertise and domain knowledge struggle to find an appropriate model for…