Search
Search Results
-
A3R-Net: adaptive attention aggregation residual network for sparse DOA estimation
In this paper, a unified deep learning framework is developed for high-precision direction-of-arrival (DOA) estimation. Unlike previous methods that...
-
H1DBi-R Net: Hybrid 1D Bidirectional RNN for Efficient Diabetic Retinopathy Detection and Classification
Nowadays the eye disease that widely affects the visual impairment of humans is Diabetes Retinopathy (DR). The advanced stage of the disorder leads...
-
ID-Net: an improved mask R-CNN model for intrusion detection under power grid surveillance
Intrusion detection is a crucial task in power grid surveillance system by providing early warning for power grid security. Construction machinery...
-
DM-Net: A Dual-Model Network for Automated Biomedical Image Diagnosis
Biomedical image segmentation is an essential task in the computer-aided diagnosis system. An encoder-decoder based on a shallow or deep...
-
Instance Segmentation of Densely Packed Cells Using a Hybrid Model of U-Net and Mask R-CNN
In malignant tumors and microbial infections, cells are commonly growing under confinement due to rapid proliferation in limited space. Nonetheless,...
-
Efficient Lung Cancer Segmentation Using Deep Learning-Based Models
The most hazardous disease the globe is now dealing with is cancerous. It is challenging to find cancerous nodules inside the lungs, although many...
-
Optimized Multifaceted Approach in Agriculture by Goal Programming with R and Python
Scheduling and organizing is a crucial part of managing the land in agriculture. To do this, crop** pattern optimization within a set of...
-
Nuclei-Net: a multi-stage fusion model for nuclei segmentation in microscopy images
In this study, we proposed Nuclei-Net: A multi-stage fusion model for segmenting nuclei in microscopy images. Our proposed model works in two stages....
-
\(R^2Net\): relative relation network with intra-class local augmentation for few-shot learning
The task of few-shot learning (FSL) is to classify never-before-seen samples by merely depending on few examples. This work, called the Relative...
-
Hybrid deep learning model for multi biotic lesions detection in solanum lycopersicum leaves
Farmers are concerned about the automatic detection of lesions and pests that threaten tomato plants. Traditional computer vision and pattern...
-
Introducing .NET for Apache Spark Distributed Processing for Massive Datasets
Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book is an introduction to both Apache Spark and the .NET...
-
Diagnosis of COVID-19 Pneumonia via a Novel Deep Learning Architecture
COVID-19 is a contagious infection that has severe effects on the global economy and our daily life. Accurate diagnosis of COVID-19 is of importance...
-
MSSIF-Net: an efficient CNN automatic detection method for freight train images
Freight trains are one of the most important modes of transportation. The fault detection of freight train parts is crucial to ensure the safety of...
-
MTCNN++: A CNN-based face detection algorithm inspired by MTCNN
Increasing security concerns in crowd centric topologies have raised major interests in reliable face recognition systems globally. In this context,...
-
Variable Selection Methods-Based Analysis of Macroeconomic Factors for an Enhanced GDP Forecasting: A Case Study of Thailand
Forecasting Gross Domestic Product (GDP) accurately is essential for understanding the behavior of an economy, but it requires considering many...
-
C++ Software Interoperability for Windows Programmers Connecting to C#, R, and Python Clients
Get up-to-speed quickly and connect modern code written in C#, R, and Python to an existing codebase written in C++. This book for practitioners is...
-
Semantic and geometric information propagation for oriented object detection in aerial images
AbstractUnlike the natural scenes, aerial objects are often in arbitrary orientations and surrounded by cluttered backgrounds, causing the...
-
A Novel Facial Expression Recognition (FER) Model Using Multi-scale Attention Network
Facial Expression Recognition (FER) faces significant challenges, primarily due to significant variations within classes and subtle visual...
-
Learning coordinated emotion representation between voice and face
Voice and face information are two most important perceptual modalities for human. In recent years, many researchers show great interest in learning...
-
