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...
To address the challenge of defect detection in tempered glass panel production rising from sample scarcity, this paper proposes a few-shot detection methodology that integrates an enhanced Stable Diffusion model with Mask R-CNN. Specifically, the ap...
The rapid quantification of nitrate nitrogen concentration plays a pivotal role in monitoring soil nutrient content. Nevertheless, the low detection efficiency limits the application of traditional methods in rapid testing. For this investigation, we...
While ship detection using high-resolution optical satellite images plays an important role in various civilian fields—including maritime traffic survey and maritime rescue—it is a difficult task due to influences of the complex backgroun...
Discarding Non-Maximum Suppression (NMS) post-processing and realizing fully end-to-end object detection is a recent research focus. Previous works have proved that the one-to-one label assignment strategy provides the chance to eliminate NMS during...
In order to improve the accuracy of pipe burst detection in water distribution networks (WDNs), a novel small sample diagnosis method (SSDM) based on the head loss ratio (HLR) method and deep transfer learning (DTL) method has been proposed. In this...
Malicious traffic detection in IoT environments faces dual challenges: limited labeled data and heterogeneous, complex traffic patterns. To address these limitations, we propose a malicious traffic detection framework, GADF-SRGA, which integrates Gra...
Owing to the rapid development of the cosmetic industry, cosmetic safety has become the focus of consumers’ attention. However, in order to achieve the desired effects in the short term, the illegal addition of hormones in cosmetics has emerged...
With the advent of drones, new potential applications have emerged for the unconstrained analysis of images and videos from aerial view cameras. Despite the tremendous success of the generic object detection methods developed using ground-based photo...
The fault detection of steam turbine blades faces severe engineering challenges, such as insufficient fault data, imbalanced class distribution, and difficulty in extracting weak damage signal features, which seriously restrict the accuracy and gener...
Under the existing single sample condition, the fatigue detection method of an automobile driver has some problems, such as an improper camera calibration method, image denoising beyond the controllable range, low fatigue detection accuracy, and unsa...
Detecting out-of-distribution (OOD) samples is critical for the deployment of deep neural networks (DNN) in real-world scenarios. An appealing direction in which to conduct OOD detection is to measure the epistemic uncertainty in DNNs using the Bayes...
Moving target detection is one of the most important tasks of radar systems. The clutter echo received by radar is usually strong and heterogeneous when the radar works in a complex terrain environment, resulting in performance degradation in moving...
The emergence of advanced machine learning or deep learning techniques such as autoencoders and generative adversarial networks, can generate images known as deepfakes, which astonishingly resemble the realistic images. These deepfake images are hard...
To address the challenges of limited samples, class imbalance, and real-time requirements in surface defect detection for solar vacuum glass collector tubes, this study proposes an improved lightweight RT-DETR-based method. Specifically, DICM is intr...
Insulator types and materials vary substantially across power system inspection scenarios, while damage defects occur infrequently; consequently, defect images that match a target insulator type and operating environment are often difficult to obtain...
Industrial anomalous sound detection is important for machine condition monitoring, especially when anomalous recordings are unavailable and only a small number of normal recordings can be collected from the target machine. This paper proposes target...
Food allergies are a severe burden for affected individuals and healthcare systems. To tackle the need for simple food allergen detection, we developed a system for the detection of the soy protein glycinin via a centrifugal microfluidics-assisted la...
Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), a major challenge for the swine industry, can be transmitted both vertically and horizontally. Common sample types, including processing fluid, serum, and family oral fluid, can neither det...
Phishing webpage detection is critical in combating cyber threats, yet distinguishing between benign and phishing webpages remains challenging due to significant feature overlap in the representation space. This study introduces a reinforced Triplet...
The detection of objects on water surfaces is a pivotal technology for the perceptual systems of unmanned surface vehicles (USVs). This paper proposes a novel real-time target detection system designed to address the challenges posed by indistinct bo...
Machine-vision-based defect detection, instead of manual visual inspection, is becoming increasingly popular. In practice, images of the upper surface of cableway load sealing steel wire ropes are seriously affected by complex environments, including...
Benzo[a]pyrene (BaP), a potent carcinogenic polycyclic aromatic hydrocarbon, is a critical food contaminant originating from environmental deposition and thermal processing, posing a significant threat to public health and driving stringent global re...
In remote sensing building detection tasks, data acquisition remains a critical bottleneck that limits both model performance and large-scale deployment. Due to the high cost of manual annotation, limited geographic coverage, and constraints of image...
A key step for broad viral detection using high-throughput sequencing (HTS) is optimizing the sample preparation strategy for extracting viral-specific nucleic acids since viral genomes are diverse: They can be single-stranded or double-stranded RNA...
To address the severe performance degradation of radar weak target detection induced by dense cluster targets and sea-spike interference in nonhomogeneous sea clutter environments, this paper proposes an enhanced Adaptive Normalized Matched Filter al...
Infrared dim and small target detection is crucial for long-range sensing. However, its deep representation learning is severely constrained by the scarcity of accurately annotated real data, and related research remains underdeveloped. Existing data...
Background: Breast cancer is a leading cause of cancer death worldwide. Several studies have demonstrated that dogs can sniff and detect cancer in the breath or urine sample of a patient. This study aims to assess whether the urine sample can be used...
Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defect...
The detection of sea mines in side-scan sonar imagery is hindered by small object size, heavy speckle noise, and severe data scarcity. Existing studies mostly transplant improvements designed for natural images to sonar scenarios, and their effective...
Tuberculosis (TB) is still one of the world’s deadliest infections. Fast detection of the pathogen M. tuberculosis (MTB) and its genetic resistance markers substantially improves treatment success and outcome. A key element for rapid genetic di...
This paper proposes DCGAN-YOLOv8n, an integrated framework that significantly advances small-sample target detection by synergizing generative adversarial feature enhancement with multi-scale representation learning. The model’s core contributi...
A simple analytical approach based on capillary zone electrophoresis with ultraviolet detection and repeated sample injection strategy (applied in a hydrodynamically closed separation system for the first time) was developed for the determination of...
Few-shot object detection (FSOD) based on fine-tuning is essential for analyzing optical remote sensing images. However, existing methods mainly focus on natural images and overlook the scale variations in remote sensing images, leading to feature co...
Automated violence detection in images presents a technical and scientific challenge that demands specialized methods to enhance classification systems. This study introduces an approach for automatically identifying relevant samples to improve the p...
Golden pompano (Trachinotus ovatus) is the largest-scale marine aquaculture fish species in China, with a significant economic and nutritional value as a high-quality seafood product. The recent outbreak of an epidemic caused by a novel Carpione rhab...
Carbon dots (CDs) are a heterogeneous family of fluorescent carbon nanomaterials that includes carbon quantum dots (CQDs) as a subclass. Owing to their favorable fluorescence, surface chemistry, and functionalization potential, CDs have been widely i...
Diagnostics often require specialized equipment and trained personnel in laboratory settings, creating a growing need for point-of-care tests (POCTs). Among the genetic testing methods available, Loop-mediated Isothermal Amplification (LAMP) offers a...
A novel anthracene-based receptor was synthesized via a facile condensation method. The anion-sensing behavior of the receptor was systematically investigated using colorimetric analysis, UV–visible spectroscopy, photoluminescence studies, and...
Acoustic event detection (AED) systems, combined with video surveillance systems, can enhance urban security and safety by automatically detecting incidents, supporting the smart city concept. AED systems mostly use mel spectrograms as a well-known e...
Detecting small objects and objects with large scale variants are always challenging for deep learning based object detection approaches. Many efforts have been made to solve these problems such as adopting more effective network structures, image fe...
Helminth infections caused by soil-transmitted species, like Ascaris lumbricoides, Trichuris trichiura, and hookworms, affect over one billion people worldwide, yet accurate diagnosis remains challenging due to low sensitivity of microscopy in detect...
Accurate field-scale crop disease detection is crucial for precise decisions and for highly efficient multi-scale collaboration. UAV-based multispectral imaging technology offers advantages in terms of high efficiency and low cost. Deep learning show...
Early detection and prompt response are key factors in the eradication of ‘huanglongbing’ (HLB) in California. Currently, qPCR testing of leaf tissue guides the removal of infected trees. However, because of the uneven distribution of &ls...
Large-scale botnet detection using graph neural networks (GNNs) often requires subgraph sampling to reduce computational and memory costs. However, conventional sampling strategies may fail to simultaneously preserve the global topology and local com...
Federated Learning (FL) presents a promising approach for collaborative intrusion detection while preserving data privacy. However, current FL frameworks face challenges with non-independent and identically distributed (non-IID) data and class imbala...
Traditional object detectors require extensive instance-level annotations for training. Conversely, few-shot object detectors, which are generally fine-tuned using limited data from unknown classes, tend to show biases toward base categories and are...
Many techniques have been studied for recovering information from shared media such as optical fiber that carries different types of communication, sensing, and data streaming. This article focuses on a simple method for retrieving the targeted infor...
This study presents a novel flexible Rayleigh–exponential mixture detection model (REMDM) for estimating population abundance under line transect sampling. The proposed detection function combines a Rayleigh-type component with an exponential c...
Insulators are an important part of transmission lines in active distribution networks, and their performance has an impact on the power system’s normal operation, security, and dependability. Traditional insulator detection methods, on the oth...
of 948