Camouflaged object detection (COD), in a broad sense, aims to detect image objects that have high degrees of similarity to the background. COD is more challenging than conventional object detection because of the high degree of “fusion” b...
This paper introduces an adaptive method for detecting front vehicles under complex weather conditions. In the field of vehicle detection from images extracted by cameras installed in vehicles, backgrounds with complicated weather, such as rainy and...
Face detection for security cameras monitoring large and crowded areas is very important for public safety. However, it is much more difficult than traditional face detection tasks. One reason is, in large areas like squares, stations and stadiums, f...
Intelligent anomaly detection is a promising area to discover anomalies as manual processing by human are generally labor-intensive and time-consuming. An effective approach to deal with is essentially to build a classifier system that can reflect th...
Fire is a destructive hazard impacting residential, industrial, and forested environments. Once ignited, fire becomes difficult to control, and recovery efforts are often extensive. Therefore, early detection is critical for effective firefighting. T...
The highlighted area or object is defined as the salient region or salient object. For salient object detection, the main challenges are still the clarity of the boundary information of the salient object and the positioning accuracy of the salient o...
Various applications, such as pollution monitoring, toxic-gas detection, noninvasive medical diagnostics and industrial process control, require sensitive and selectivedetection of gas traces with concentrations in the parts in 109 (ppb) and sub-ppb...
This paper presents a novel architecture for detecting mathematical formulas in document images, which is an important step for reliable information extraction in several domains. Recently, Cascade Mask R-CNN networks have been introduced to solve ob...
Detecting violent content in audio recordings is crucial for public safety, autonomous surveillance, and content moderation, particularly when visual cues are unreliable or unavailable. A resource-aware two-stage cascade system is proposed for acoust...
To address the challenges of small fastener targets, complex backgrounds, and the low efficiency of traditional manual inspection in coating workshop scenarios, this paper proposes an improved Cascade R-CNN-based fastener detection method. A VOC-form...
The increasing activity of unmanned aerial vehicles (UAVs) has intensified the demand for reliable and computationally efficient methods for passive radio-frequency (RF) signal detection. In practical RF monitoring scenarios, the environment is often...
Traditional single-tree detection methods usually need to set different thresholds and parameters manually according to different forest conditions. As a solution to the complicated detection process for non-professionals, this paper presents a singl...
In this study, novel fluorescent DNA biosensors for mercury (Hg2+) and silver (Ag+) ions were developed based on thymine (T)- and cytosine (C)-rich recognition elements in combination with exonuclease III and a mismatch-catalyzed hairpin assembly (MC...
Detecting dynamic and amorphous objects like fire and smoke poses significant challenges in object detection. To address this, we propose Dual-Path Cascade Stochastic DETR (Dual-Path CSDETR). Unlike Cascade DETR, our model introduces cascade stochast...
Object detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detec...
In roadside surveillance imagery, shadows, vegetation, vehicles, exposed pavement, and water stains may exhibit local textures and morphological characteristics similar to those of rockfalls, causing a standalone You Only Look Once (YOLO) real-time o...
Rapid and accurate tree-crown detection is significant to forestry management and precision forestry. In the past few decades, the development and maturity of remote sensing technology has created more convenience for tree-crown detection and plantin...
In the realm of power grid construction, the accurate inspection of critical components within overhead transmission lines holds paramount significance and also serves as a cornerstone for safeguarding the safety and stability of the power system and...
Zero-day intrusion detection is still a difficult task because of the difference between high laboratory precision and real-time deployability under strict operational constraints. This paper proposes a lightweight two-stage cascade architecture that...
Foodborne pathogens represent a class of pathogenic microorganisms capable of causing food poisoning or serving as foodborne vectors, constituting a major source of food safety concerns. With increasing demands for rapid diagnostics, conventional cul...
Scene text detection is an important research field in computer vision, playing a crucial role in various application scenarios. However, existing scene text detection methods often fail to achieve satisfactory results when faced with text instances...
Immobilizing enzymes with nanozymes to catalyze cascade reactions overcomes many of the shortcomings of biological enzymes in industrial manufacturing. In the study, glucose oxidases were covalently bound to FeS2 nanozymes as immobilization carriers...
In this paper, a high-precision 3D object detector—Voxel–RCNN—is adopted as the baseline detector, and an improved detector named RCAVoxel-RCNN is proposed. To address various issues present in current mainstream 3D point cloud voxe...
Standoff chemical detection and identification techniques are necessary for ensuring safe exposure to dangerous substances. Molecular fingerprints of unknown chemicals can be measured using wavelength-tunable quantum cascade lasers operating in long-...
LiDAR-based 3D object detection remains challenging due to sparse and irregular point cloud distributions, which degrade detection accuracy for small and occluded objects. In view of this, this paper proposes a novel two-stage voxel-based 3D detector...
The integration of advanced materials and signaling cascade strategies is a promising and highly relevant topic for enhancing the performance of bioanalysis. In this study, a three-stage cascade amplification electrochemical bioanalysis (TCAE-bioanal...
Table detection is a preliminary step in extracting reliable information from tables in scanned document images. We present CasTabDetectoRS, a novel end-to-end trainable table detection framework that operates on Cascade Mask R-CNN, including Recursi...
Roll-to-roll (R2R) manufacturing processes demand precise control of web or yarn velocity and tension, alongside robust mechanisms for handling system failures. This paper presents an integrated approach combining high-performance control with reliab...
As the unique identifier of individual breeding pigs, the loss of ear tags can result in the loss of breeding pigs’ identity information, leading to data gaps and confusion in production and genetic breeding records, which can have catastrophic...
Herein, an ultrasensitive DNAzyme-based fluorescence biosensor for detecting Cu2+ was designed using the cascade signal amplification strategy, coupling λ-exonuclease-assisted target recycling and mismatched catalytic hairpin assembly (MCHA)....
Pipelines are one of the most efficient and economical methods of transporting fluids, such as oil, natural gas, and water. However, pipelines are often subject to leakage due to pipe corrosion, pipe aging, pipe weld defects, or damage by a third-par...
Change detection is an important application of remote sensing image interpretation, which identifies changed areas of interest from a pair of bi-temporal remote sensing images. Various deep-learning-based approaches have demonstrated promising resul...
Object detection is an essential computer vision task that aims to detect target objects from an image. The traditional models are insufficient to generate a high-quality anchor box. To solve the problem, we propose a novel joint model called guided...
Deep-learning-based object detectors have substantially improved state-of-the-art object detection in remote sensing images in terms of precision and degree of automation. Nevertheless, the large variation of the object scales makes it difficult to a...
Although the face detection problem has been studied for decades, searching tiny faces in the whole image is still a challenging task, especially in low-resolution images. Traditional face detection methods are based on hand-crafted features, but the...
This article presents the efficiency of using cascaded neural structures in the process of detecting damage to electrical circuits in a squirrel cage induction motor (IM) supplied from a frequency converter. The authors present the idea of a sequenti...
Pest infestation poses significant threats to grain storage due to pests’ behaviors of feeding, respiration, excretion, and reproduction. Efficient pest detection and control are essential to mitigate these risks. However, accurate detection of...
Saliency detection is a key research topic in the field of computer vision. Humans can be accurately and quickly mesmerized by an area of interest in complex and changing scenes through the visual perception area of the brain. Although existing salie...
High-resolution remote sensing images can not only help forestry administrative departments achieve high-precision forest resource surveys, wood yield estimations and forest mapping but also provide decision-making support for urban greening projects...
Anomaly detection in industrial imaging is critical for ensuring quality and reliability in automated manufacturing processes. While recently several methods have been reported in the literature that have demonstrated impressive detection performance...
Ensemble learning is an important group of machine learning techniques that aim to enhance the nonlinearity and generalization ability of a learning system by aggregating multiple learners. We found that ensemble techniques show great potential for i...
Vehicular ad hoc networks (VANETs) incorporating vehicles as an active and fast topology are gaining popularity as wireless communication means in intelligent transportation systems (ITSs). The cybersecurity issue in VANETs has drawn attention due to...
Infrared and visible images (multi-sensor or multi-band images) have many complementary features which can effectively boost the performance of object detection. Recently, convolutional neural networks (CNNs) have seen frequent use to perform object...
Traffic surveillance cameras, as core sensing devices in smart cities, are crucial for traffic management, violation detection, and autonomous driving. However, due to deployment constraints and hardware limitations, the videos they capture often suf...
The increasing use of multi-parallel grid-connected inverters introduces both high-quality and high-capacity power, while it tends to cause a resonance instability problem. A resonance damper can virtualize a resistor at resonant frequency to suppres...
This research proposed the design, fabrication, and experiments of a surface acoustic wave resonator (SAWR)-based multi-sized particles monitor. A wide range selection and monitoring of large coarse particles (LCP), inhalable particles (PM10), and fi...
Generic object detection algorithms for natural images have been proven to have excellent performance. In this paper, fabric defect detection on optical image datasets is systematically studied. In contrast to generic datasets, defect images are mult...
In this study, a sliding microfluidic biosensor integrating RPA-SDA cascaded amplification was developed for the rapid, visual detection of Shigella. A novel RPA primer targeting the specific ipaH gene was designed to include a 5′-end G-quadrup...
A hyperspectral image usually covers a large scale of ground scene, which contains various materials with different spectral properties. When directly exploring the background information using all the image pixels, complex spectral interactions and...
Pedestrian detection is a challenging task, mainly owing to the numerous appearances of human bodies. Modern detectors extract representative features via the deep neural network; however, they usually require a large training set and high-performanc...
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