Academic Articles & Research Papers

Link Predictions with Bi-Level Routing Attention

Background/Objectives: Knowledge Graphs (KGs) are often incomplete, which can significantly impact the performance of downstream applications. Manual completion of KGs is time-consuming and costly, emphasizing the importance of developing a...

Artificial intelligence-based masked face detection: A survey

The COVID-19 virus is causing a global pandemic. The total number of new coronavirus cases worldwide by the end of November 2020 had already surpassed 60 million. The World Health Organization (WHO) has determined that wearing masks is a cr...

Culling Double Counting in Sequence Images for Fruit Yield Estimation

Exact yield estimation of fruits on plants guaranteed fine and timely decisions on harvesting and marketing practices. Automatic yield estimation based on unmanned agriculture offers a viable solution for large orchards. Recent years have w...

Autonomous Driving Roadway Feature Interpretation Using Integrated Semantic Analysis and Domain Adaptation

Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking f...

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

Computer Vision

Abstract: Computer vision is a field of artificial intelligence that focuses on enabling computers to understand and interpret visual information from images or videos. It involves developing algorithms and techniques to extract meaningful ...

Machine Learning in Computer Vision: A Review

INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines...

Transformer in Computer Vision

Transformer is widely used in Natural Language Processing (NLP), in which numerous papers have been proposed. Recently, the transformer has been borrowed for many computer vision tasks. However, there are few papers to give a comprehensive ...

TranSDet: Toward Effective Transfer Learning for Small-Object Detection

Small-object detection is a challenging task in computer vision due to the limited training samples and low-quality images. Transfer learning, which transfers the knowledge learned from a large dataset to a small dataset, is a popular metho...

Research progress and trends of deep learning based wireless communication receiving method

With the continues expansion of the application boundary for wireless communications, the application environment of wireless communications is becoming increasingly complex and diverse, which faces negative impacts such as radio frequency ...

UPANets: Learning from the Universal Pixel Attention Neworks

With the successful development in computer vision, building a deep convolutional neural network (CNNs) has been mainstream, considering the character of shared parameters in a convolutional layer. Stacking convolutional layers into a deep ...

An Input-Perceptual Reconstruction Adversarial Network for Paired Image-to-Image Conversion

Image-to-image conversion based on deep learning techniques is a topic of interest in the fields of robotics and computer vision. A series of typical tasks, such as applying semantic labels to building photos, edges to photos, and raining t...

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...

A Methodological Review on Prediction of Multi-Stage Hypovigilance Detection Systems Using Multimodal Features

Several hypovigilance detection systems (HDx) were developed to avoid road-side accidents due to driver fatigue. They have suffered from several limitations. Notably many of these are focused on center-head position to define an area of int...

MSDNet: A Multi-Scale Feature Representation Network Model for Tunnel Bolt Detection

Bolts are critical components of tunnel linings, essential for ensuring safe tunnel operation. Due to their susceptibility to corrosion and detachment, it is vital to closely monitor them during maintenance. However, identifying a large num...

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...

Optimal Frontier-Based Autonomous Exploration in Unconstructed Environment Using RGB-D Sensor

Aerial robots are widely used in search and rescue applications because of their small size and high maneuvering. However, designing an autonomous exploration algorithm is still a challenging and open task, because of the limited payload an...

Computer Vision – ACCV 2006

An information bottleneck-based optimal transport network for automated diagnosis of spinal diseases.

A novel nondestructive detection approach for seed cotton lint percentage using deep learning

Abstract Background The lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consumi...