IEEE

PGSMamba: Prompt-Guided Shuffle State Space Model for Hyperspectral Image Classification

Abstract: Hyperspectral image classification demands models capable of efficiently capturing complex spectral–spatial relationships and long-range dependencies. Despite significant advances in CNNs ...
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

A Lightweight MobileViT with a Dual-Path Attention Mechanism for MRI Image Classification ()

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...
IEEE

CNN-Based Retinal Image Classification for Anemia Detection

Abstract: Anemia is a global health concern impacting vulnerable populations which necessitates improved diagnostic methods beyond traditional approaches such as complete blood count. This study ...
IEEE

CNN-Based Image Forgery Detection Using Sequential Deep Learning Architecture

Abstract: The wide availability of digital image editing tools and software has made it highly straightforward to tamper with or modify digital media or photographic evidence, which shows that it is ...
IEEE

CNN-based vessel tracking in infrared images with an unmanned wing-in-ground vehicle

Abstract: The urge for the development of unmanned autonomous vehicles that can satisfy the needs of the supply chains, covering distances in the shortest time possible while being environmentally ...
IEEE

Transformer-Embedded Attentive CNN for Spectral Image Analysis of Rice Blast Syndromes

Abstract: Leaf blast disease is a significant constraint in world-wide rice production systems, necessitating effective monitoring for optimized crop-yield management. Satellite-derived land-surface ...
IEEE

Deep Learning Approaches for Multi-Label Classification of Ophthalmic Diseases: A Systematic Review and Future Directions using Retinal Images

Abstract: Ophthalmic diseases are a major contributor of blindness and visual impairment globally. Effective treatment and halting the progression of the disease depend on an early and precise ...
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

Bridging CNN and Transformer With Cross-Attention Fusion Network for Hyperspectral Image Classification

Abstract: Feature representation is crucial for hyperspectral image (HSI) classification. However, existing convolutional neural network (CNN)-based methods are limited by the convolution kernel and ...
IEEE

Image Classification using Quantum Convolutional Neural Network (QCNN)

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...