IEEE

Asymmetric Mamba–CNN Collaborative Architecture for Large-Size Remote Sensing Image Semantic Segmentation

Large-size remote sensing images contain rich geographical information. Efficient and accurate semantic segmentation of these images is of significant importance in various fields. However, the ...
IEEE

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision Xlstm and Heteromodal Variational Encoder-Decoder

Abstract: Neurogliomas are among the most aggressive forms of can-cer, presenting considerable challenges in both treatment and monitoring due to their unpredictable biological behav-ior. Magnetic ...
IEEE

SPNet: Sparse-mask Prompt-learning Network for Cerebrovascular Segmentation

Abstract: Cerebrovascular segmentation demands a comprehensive understanding of vascular topology from a global perspective on 3D Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) images.
IEEE

Probabilistic Forecasting for Battery Health Estimation Using CNN-LSTM on Augmented Multi-Operation Data

Abstract: Ensuring the safety and reliability of electric vehicles and energy storage systems requires an effective evaluation of lithium-ion battery State of Health (SOH). Most current methods are ...
IEEE

Data-Driven Solutions for Human Trafficking: Detection and Impact Analysis Using Machine Learning

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
IEEE

Emotion Recognition from Speech Signals Using Hybrid CNN Model

Abstract: The fast growth of internet and communications networks has drastically enhanced data transport, allowing tasks like Speech Emotion Recognition (SER), an essential aspect of human-computer ...
IEEE

Learning Domain Generalized Remote Sensing Image Segmentation by Multiscale Instance Disentanglement

Abstract: Remote sensing image segmentation is a fundamental task in Earth observation. Rapid development has been made in the past decade owing to the deep learning techniques. Most of the existing ...