News

IEEE1d
Speckle Noise Reduction for Medical Ultrasound Images Using Hybrid CNN-Transformer Network - IEEE Xplore
This paper proposes a hybrid CNN-transformer network called HCTSpeckle, an encoder-decoder network with a fusion block designed to enhance ultrasound images. The fusion block combines swin ...
IEEE3d
A Symmetry-Aware Pitch Feature Encoder–Decoder Network for Condition Monitoring of Pitch Bearings in Wind Turbines - IEEE Xplore
Pitch bearing is one of the critical components of the electric pitch system in wind turbines (WTs), and its early and reliable fault warning is of great significance to ensure the operational ...
IEEE4d
Unsupervised Feature Selection using Encoder-Decoder Networks
Feature selection is one of the most important techniques for dimension reduction in a wide range of tasks. This paper presents a simple yet efficient method for unsupervised feature selection. To ...
IEEE5d
BEFNet: A Hybrid CNN-Mamba Architecture for Accurate Skin Lesion Image Segmentation - IEEE Xplore
Accurate image segmentation of skin lesions is crucial for the detection and treatment of skin cancer. Based on the modern state space model Mamba, a novel hybrid CNN-Mamba network (BEFNet) is ...
IEEE5d
A Robust CNN Framework for Change Detection Analysis From Bitemporal Remote Sensing Images - IEEE Xplore
Deep learning (DL) algorithms are currently the most effective methods for change detection (CD) from high-resolution multispectral (MS) remote-sensing (RS) images. Because a variety of satellites are ...
IEEE7d
Mesoscale Eddy Detection and Classification From Sea Surface Temperature Maps With Deep Neural Networks - IEEE Xplore
Oceanic eddies are a widespread and important occurrence that plays a vital role in the movement of chemicals and energy within the marine ecosystem. Hence, the astute and precise recognition of these ...
IEEE7d
On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures - IEEE Xplore
Recent advances in generalized image understanding have seen a surge in the use of deep convolutional neural networks (CNN) across a broad range of image-based detection, classification and prediction ...
IEEE9d
Encoder-Decoder Neural Network Architecture for solving Job Shop Scheduling Problems using Reinforcement Learning - IEEE Xplore
This paper proposes an Encoder-Decoder neural network architecture with Attention Mechanism for solving the DRC-FJSSP using Deep Q-Learning. In the DRC-FJSSP the number of operations to schedule is ...
IEEE10d
Estimator-Based Encoder-Decoder for Reducing Communications Demands in Event-triggered Networked Control Systems - IEEE Xplore
Wireless networks are vital for implementing flexible Networked Controlled Systems (NCS) in distributed applications, yet they introduce sampling errors, delays, and packet losses that can compromise ...
IEEE10d
On the feasibility of classifying flows in software-defined data center networks by an encoder-only architecture - IEEE Xplore
Classifying elephant and mouse flows is pivotal for meeting Quality of Service requirements in Software-Defined Data Center Networks. Diverse approaches have addressed this classification problem by ...
IEEE14d
A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images - IEEE Xplore
The fully convolutional network (FCN) with an encoder-decoder architecture has been the standard paradigm for semantic segmentation. The encoder-decoder architecture utilizes an encoder to capture ...
IEEE14d
Attention Guided Encoder-Decoder Network With Multi-Scale Context Aggregation for Land Cover Segmentation - IEEE Xplore
Land cover segmentation is an important and challenging task in the field of remote sensing. Even though convolutional neural networks (CNNs) provide great support for semantic segmentation, standard ...