Communications of the ACM

Where Are the City Trees? Monitoring Urban Trees across the U.S. Using Generative AI

Urban trees are critically important to mitigate poor air quality, excessive heat islands, and unmoderated rainwater overflow ...
IEEE

Novel Mask R-CNN Based Mushroom Cluster Tracking in Time-Lapse Images From a Farm Environment

Abstract: This study aims to develop a novel deep learningbased approach to support the automated mushroom growth monitoring using an object tracking algorithm in conjunction with instance ...
Scientific Research Publishing

H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation ()

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...
IEEE

Flood Area Segmentation using Using U-Net: A Deep Learning Approach with UAV and Satellite Imagery

Abstract: Flood area segmentation plays a critical role in disaster management and mitigation, providing valuable insights for timely interventions and resource allocation during flood events. This ...
IEEE

CNN-LSTM-Attention-based Vehicle Weight Estimation using Weigh-in-Motion

Abstract: Vehicle weight significantly impacts load distribution on road surfaces and collision forces in traffic accidents, thereby influencing structural integrity and injury risk. While advanced ...
IEEE

MCBL-UNet: A Hybrid Mamba-CNN Boundary Enhanced Light-weight UNet for Placenta Ultrasound Image Segmentation

Abstract: The shape and size of the placenta are closely related to fetal development in the second and third trimesters of pregnancy. Accurately segmenting the placental contour in ultrasound images ...
IEEE

Real Time Traffic Management System using Mask R-CNN and Dynamic Scheduling Algorithm

Abstract: Conventional manual, semi automated and timed traffic control systems are being replaced by more effective technology based systems. A low cost, real time, automated system is necessary for ...
IEEE

Hybrid CNN-Transformer Model for Accurate Classification of Human Attention Levels Using Workplace EEG Data

Abstract: Accurately detecting human attention levels is a key challenge in cognitive neuroscience, with broad application value in improving productivity. Although Electroencephalography (EEG) ...
IEEE

LFSSMam: Efficient Aggregation of Multi-Spatial-Angular-Modal Information Using Selective SSM for Light Field Semantic Segmentation

Abstract: Efficiently aggregating 4D light field information to achieve accurate semantic segmentation has always faced challenges in capturing long range dependency information (CNN-based) and the ...
IEEE

EICSeg: Universal Medical Image Segmentation via Explicit In-Context Learning

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
IEEE

An Evaluation of Medical Image Analysis using Image Segmentation and Deep Learning Techniques for Brain-Tumour

Abstract: An aberrant mass of rapidly proliferating brain cells, known as a brain tumour, may develop into various forms of cancer. The segmentation of brain tumours by MRI scans is a challenging but ...
IEEE

Efficient Satellite Image Retrieval Using Shearlet Transforms and Spiking Neurons-Based Liquid Autoencoder Model

Abstract: This paper introduces an innovative content-based image retrieval system for precise and effective retrieval of satellite images. The system integrates liquid autoencoders with shearlet ...