eLife

Predicting human decision-making across task conditions via individuality transfer

Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of decision-making patterns across distinct task conditions.
IEEE

Hybrid CNN-Transformer Model for Multi-Scale Environmental Impact Assessment in Circular Waste Management Systems

Abstract: The assessment of the impact of the circular waste management system cannot be done by the conventional methods of impact assessment due to the stochastic distribution of waste and the ...
IEEE

An Interpretable Hybrid CNN-SVM Model for Predicting Stress Among University Students

Abstract: Stress among university students can be defined as a state of mental tension caused by difficult academic endeavours. Nonetheless, stress at the tertiary (i.e., University) level has been ...
IEEE

Regional Tropospheric Delay Prediction Model Based on LSTM-Enhanced Encoder Network

Abstract: Precise modeling of zenith tropospheric delay (ZTD) is essential for real-time high-precision positioning in global navigation satellite systems. Due to the stochastic variability of ...
IEEE

BR-Mix3DNet: Predicting Breast Neoadjuvant Chemotherapy Response With a Hybrid MLP-Mixer and 3D CNN Model

Abstract: Neoadjuvant chemotherapy (NAC) is the standard treatment for locally advanced and inflammatory breast cancer, as well as early-stage triple-negative breast cancer (TNBC) and human epidermal ...
IEEE

An Optimized Model With Encoder-Decoder ConvLSTM for Global Ionospheric Forecasting

Abstract: The ionosphere is vital for satellite navigation and radio communication, but observational limitations necessitate ionospheric forecasting. The least squares collocation (LSC) method is ...
IEEE

Chinese to English Machine Translation using Boundary-Assistant Encoder-Decoder Network with Embeddings from Language Models

Abstract: In recent years, translation of text from one language to another without human involvement is done automatically through Artificial Intelligence (AI) which is defined as English Machine ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

DE-Unet: Dual-Encoder U-Net for Ultra-High Resolution Remote Sensing Image Segmentation

Abstract: In recent years, there has been a growing demand for remote sensing image semantic segmentation in various applications. The key to semantic segmentation lies in the ability to globally ...
IEEE

A Hybrid CNN-LSTM Multi-Modal for Early Detection and Recurrence Prediction of Ovarian Cancer and Model Transparency using SHAP and LIME

Abstract: Ovarian cancer is one of the deadliest cancers in women because it shows no clear symptoms in the early stages and often returns after treatment. Current detection methods are not strong ...
IEEE

Hybrid CNN-LSTM Model for Accurate Time Series Forecasting: A Deep Learning Approach

Abstract: Time series data analysis is essential in a variety of fields, such as finance, meteorology, and healthcare. Traditional methods often struggle to capture the complex temporal correlations ...
IEEE

Deep Learning Meets Traditional AI: A Hybrid CNN-RF Model for Accurate and Explainable Skin Lesion Classification

Abstract: In dermatology, the task of skin lesion classification is a very important one, for early detection and treatment of skin cancer. In this work, we propose a hybrid AI model where ...