81 Result(s)
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Article
Open AccessDuet of ViT and CNN: multi-scale dual-branch network for fine-grained image classification of marine organisms
Fine-grained image classification of marine organisms involves dividing subcategories within a larger category. For instance, this could mean distinguishing specific species of fish or types of algae. This typ...
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Chapter and Conference Paper
AI-Based Intelligent-Annotation Algorithm for Medical Segmentation from Ultrasound Data
The management of prostate cancer, a prevalent source of mortality in men, calls for meticulous delineation of the prostate in transrectal ultrasound (TRUS) images for effective treatment planning. This paper ...
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Chapter and Conference Paper
Verifiable Attribute-Based Proxy Re-encryption with Non-repudiation Based on Blockchain
With the development of Blockchain, cloud computing, and artificial intelligence, smart transportation is highly likely to drive urban transportation in the direction of intelligence and digitalization. Howeve...
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Chapter and Conference Paper
Collaborative Path Planning for Multi-UAVs by Evolutionary Computing
This paper addresses the challenges of path planning and cooperative control for multiple Unmanned Aerial Vehicles (UAVs) operating in large scale environments. Given the unique characteristics of large-scale ...
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Chapter and Conference Paper
BotRGA: Neighborhood-Aware Twitter Bot Detection with Relational Graph Aggregation
With the rapid development of AI-based technology, social bot detection is becoming an increasingly challenging task to combat the spread of misinformation and protect the authenticity of online resources. Exi...
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Chapter and Conference Paper
Blockchain-Based Hierarchical Access Control with Efficient Revocation in mHealth System
With the development of information technology, people can share their health records (PHRs) through the Internet and obtain rapid medical services, which makes mobile health become a promising field. PHRs are...
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Article
A broader study of cross-domain few-shot object detection
Latest studies on few-shot object detection (FSOD) mainly focuses on achieving better performance in novel class through few-shot fine-tuning. This approach is based on the large amount of annotated data in ba...
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Article
A novel DAVnet3+ method for precise segmentation of bladder cancer in MRI
Muscular invasion is a critical factor in the surgical selection of bladder cancer (BC) patients. Precise segmentation of bladder outer wall (OW), bladder inner wall (IW) and bladder tumor (BT) using MRI is an...
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Article
Open AccessUnderwater computational imaging: a survey
With the increasingly urgent demand for marine research and development, optical imaging technology remains crucial for underwater close-range information detection. However, the inherent obstacles of light tr...
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Article
Machine learning-based AI approaches for personalized smart education systems using entropy and TOPSIS approach
We know that in today's technologically sophisticated world, artificial intelligence (AI) and machine learning (ML)-based methods are serving a very positive role in executing challenging and time-consuming ta...
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Article
Disentangling latent space better for few-shot image-to-image translation
In an unpaired image-to-image translation, the main concept is to learn an underlying map** between the source and target domains. Previous approaches required large numbers of data from both domains to lear...
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Chapter and Conference Paper
BFNet: A Lightweight Barefootprint Recognition Network
In recent years, barefootprint-based biometrics has emerged as a novel research area. Compared with other biometrics, barefootprints are more covert and secure. However, due to the absence of large-scale datas...
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Chapter and Conference Paper
Spectrum Analysis on Electricity Consumption Periods by Industry in Fujian Province
Electricity is the basic energy for urban economic development and people's daily life. Exploring periods of electricity consumption has a great significance in improving quality of life, promoting industry de...
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Chapter and Conference Paper
A Matrix Factorization-Based Drug-Virus Link Prediction Method for SARS-CoV-2 Drug Prioritization
Matrix factorization (MF) has been widely used in drug discovery for link prediction, which aims to reveal new drug-target links by integrating drug-drug and target-target similarity information with a drug-ta...
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Chapter and Conference Paper
A Monocular Vision Ranging Method Related to Neural Networks
This paper proposes a neural network-based monocular vision ranging method for the situation of large camera calibration and distance variation in monocular vision ranging. The imaging size of the correspondin...
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Chapter and Conference Paper
Sternal Fracture Recognition Based on EfficientNetV2 Fusion Spatial and Channel Features
Fractures are one of the most common injuries in medicine. A fracture is a partial or complete break in the continuity of bone structure. Fractures can occur for many reasons. For example, a certain part of th...
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Chapter and Conference Paper
MFMGC: A Multi-modal Data Fusion Model for Movie Genre Classification
Movie Genre Classification (MGC) is a classic multi-label task that aims to classify movies into different genres. Existing studies have proposed many approaches for this task based on multi-modal data (e.g., ...
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Chapter and Conference Paper
A Method for Classification of Skin Cancer Based on VisionTransformer
Human skin, long exposed to air and sunlight, is the body’s first line of defense against natural hazards, which may be breached in a variety of ways, leading to cancer. According to the current level of clini...
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Chapter and Conference Paper
Emotion Recognition from Multi-channel EEG via an Attention-Based CNN Model
People’S daily communication is inseparable from emotional interaction, and good results can be achieved by using EEG signals for emotion recognition. To this end, this paper proposes an EEG emotion recognitio...
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Chapter and Conference Paper
Infrared Image Object Detection of Vehicle and Person Based on Improved YOLOv5
Existing object detection algorithms are difficult to perform object detection tasks on embedded devices under the limitations of energy efficiency ratio and power consumption due to complex network structure ...
