With the advancement of deep learning technology, the importance of utilizing deep learning for livestock management is becoming increasingly evident. goat face detection provides a foundation for goat recognition and management. In this study, we pr...
Small target detection in Unmanned Aerial Vehicle (UAV) applications is often plagued by inherent challenges such as small object sizes, sparse information, and complex background interference. Traditional detection algorithms and existing YOLO serie...
In recent years, with the rapid development of deep learning and its outstanding capabilities in target detection, innovative methods have been introduced for infrared dim small target detection. This review comprehensively summarizes public datasets...
Although infrared small target detection has been broadly used in airborne early warning, infrared guidance, surveillance and tracking, it is still an open issue due to the low signal-to-noise ratio, less texture information, background clutters, and...
Due to the inherent limitations of detection networks and the imbalance in training data, small-target detection has always been a challenging issue in the field of target detection. To address the issues of false positives and missed detections in s...
Reliable infrared small target detection plays an important role in infrared search and track systems. In recent years, most target detection methods usually use the statistical features of a rectangular window to represent the contrast between the t...
Infrared small target detection (IRSTD) is crucial for applications in security surveillance, unmanned aerial vehicle identification, military reconnaissance, and other fields. However, small targets often suffer from resolution limitations, backgrou...
In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared image...
Small targets exist in large numbers in various fields. They are broadly used in aerospace, video monitoring, and industrial detection. However, because of its tiny dimensions and modest resolution, the precision of small-target detection is low, and...
Hyperspectral imaging systems frequently rely on spectral rather than spatial resolving power for identifying objects within a scene. A hyperspectral imaging system’s response to point targets under flight conditions provides a novel technique...
Moving target detection plays a primary and pivotal role in avionics visual analysis, which aims to completely and accurately detect moving objects from complex backgrounds. However, due to the relatively small sizes of targets in aerial video, many...
Small-target detection suffers from the problems of low average precision and difficulties detecting targets from airport-surface surveillance videos. To address this challenge, this study proposes a small-target detection model based on an attention...
Target detection in UAV aerial photography scenarios faces challenges of small targets and complex backgrounds. Thus, we proposed an improved YOLOv11n small-target detection algorithm. First, a detection head is added to the 160 × 160 resolutio...
At present, the existing methods have many limitations in small target detection, such as low accuracy, a high rate of false detection, and missed detection. This paper proposes the KPE-YOLOv5 algorithm aiming to improve the ability of small target d...
Small targets in long-distance aerial photography have the problems of small size and blurry appearance, and traditional object detection algorithms face great challenges in the field of small-object detection. With the collection of massive data in...
The images captured using UAVs during inspection often contain a great deal of small targets related to transmission lines. These vulnerable elements are critical for ensuring the safe operation of these lines. However, due to various factors such as...
Unmanned aerial vehicle (UAV) targets are typically small in size, occupy only a limited pixel area, and are often located in complex environments. Existing models, however, tend to overlook smaller targets in complex backgrounds, making it easy to m...
In order to solve the problem of low accuracy of small target detection in traditional target detection algorithms, the YOLOX algorithm combined with Convolutional Block Attention Module (CBAM) is proposed. The algorithm first uses CBAM on the shallo...
Infrared dim and small target detection is a key technology for various detection tasks. However, due to the lack of shape, texture, and other information, it is a challenging task to detect dim and small targets. Recently, since many traditional alg...
To detect and recognize small-size and submerged complex background targets in infrared images, we combine a dynamic receptive field fusion strategy and a multi-scale feature fusion mechanism to improve the detection performance of small targets sign...
The human visual attention system plays an important role in infrared target recognition because it can quickly and accurately recognize infrared small targets and has good scene adaptability. This paper proposes an infrared small target detection me...
Infrared detection, known for its robust anti-interference capabilities, performs well in all weather conditions and various environments. Its applications include precision guidance, surveillance, and early warning systems. However, detecting infrar...
Infrared detection plays an important role in the military, aerospace, and other fields, which has the advantages of all-weather, high stealth, and strong anti-interference. However, infrared dim-small-target detection suffers from complex background...
For the detection of small targets, fire-like and smoke-like targets in forest fire images, as well as fire detection under different natural lights, an improved Fire-YOLO deep learning algorithm is proposed. The Fire-YOLO detection model expands the...
Aiming at the problems of small-sized ships (such as small patrol boats) in complex open-sea backgrounds, including small sizes, insufficient feature information, and high missed detection rates, this paper proposes a maritime small target image dete...
The application of image recognition technology plays a vital role in agricultural disease identification. Existing approaches primarily rely on image classification, object detection, or semantic segmentation. However, a major challenge in current s...
Deep-learning methods have exhibited exceptional performance in numerous target-detection domains, and their application is steadily expanding to include infrared small-target detection as well. However, the effect of existing deep-learning methods i...
The robust detection of small targets is one of the crucial techniques in an infrared system. It is still a challenge to detect small targets under complex backgrounds. Aiming at the problem where infrared small target detection is easily disturbed b...
Compared to wide-field telescopes, small-field detection systems have higher spatial resolution, resulting in stronger detection capabilities and higher positioning accuracy. When detecting by small fields in synchronous orbit, both space debris and...
General target detection with deep learning has made tremendous strides in the past few years. However, small target detection sometimes is associated with insufficient sample size and difficulty in extracting complete feature information. For safety...
Infrared small target detection occupies an important position in the infrared search and track system. The most common size of infrared images has developed to
With the flourish of deep learning, transformer models have achieved remarkable performance in dealing with many computer vision tasks. However, their applications in infrared small target detection is limited due to two factors: (1) the high computa...
The targets in the aerial view of UAVs are small, scenes are complex, and background noise is strong. Additionally, the low computational capability of UAVs is challenged when trying to meet the requirements of large neural networks. Therefore, a lig...
Infrared small-target detection is a key technology for the infrared search and track system (IRST), but some problems still exist, such as false detections in complex backgrounds and clutter. To solve these problems, a novel image patch tensor (IPT)...
Detecting small targets in infrared images presents significant challenges due to their tiny size and complex backgrounds, making this task a hotspot for research. Traditional methods rely on assumption-based modeling and manual design, struggling to...
Using infrared technology to accurately detect small weak targets is crucial in various fields, such as reconnaissance and security. However, the infrared detection of small weak targets is challenged by complex backgrounds, tiny target sizes, and lo...
It is a big challenge to detect and track small infrared marine targets in non-stationary and time-varying sea clutter because the signal is too strong to be estimated. Based on the phenomenon that sea clutter spreads not only in the temporal domain...
Infrared small target detection under complex backgrounds remains challenging due to the extremely small target size and low contrast with the surrounding background. These factors make contour information difficult to extract and often cause target...
Infrared small-target detection plays a crucial role in applications such as public safety monitoring. However, it faces significant challenges due to the loss of target features, which weakens detection performance. To tackle this problem, this stud...
In infrared (IR) guidance and target tracking systems, dim target intensity and complex background clutter are some of the typical challenges, especially for the accurate detection of small objects. In this article, we propose a novel IR target detec...
At present, rice is generally in a state of dense adhesion and small granular volume during processing, resulting in no effective semantic segmentation method for rice to extract complete rice. Aiming at the above problems, this paper designs a small...
Unmanned Aerial Vehicle (UAV) infrared detection has problems such as weak and small targets, complex backgrounds, and poor real-time detection performance. It is difficult for general target detection algorithms to achieve the requirements of a high...
The technology of infrared dim- and small-target detection is irreplaceable in many fields, such as those of missile early warning systems and forest fire prevention, among others. However, numerous components interfere with infrared imaging, present...
In the intricate and dynamic infrared imaging environment, the detection of infrared dim and small targets becomes notably challenging due to their feeble radiation intensity, intricate background noise, and high interference characteristics. To tack...
The detection of small infrared targets lacking texture and shape information in the presence of complex background clutter is a challenge that has attracted considerable research attention in recent years. Typical deep learning-based target detectio...
Robust and efficient detection of small infrared target is a critical and challenging task in infrared search and tracking applications. The size of the small infrared targets is relatively tiny compared to the ordinary targets, and the sizes and app...
Sonar is the primary tool used for detecting small targets at long distances underwater. Due to the influence of the underwater environment and imaging mechanisms, sonar images face challenges such as a small number of target pixels, insufficient dat...
Infrared small target detection (IRSTD) aims to extract weak small targets from complex backgrounds, and has significant practical application value in safety-critical fields such as traffic monitoring and maritime search and rescue. However, due to...
The research of infrared image small-target detection is of great significance to security monitoring, satellite remote sensing, infrared early warning, and precision guidance systems. However, small infrared targets occupy few pixels and lack color...
In recent years, data-driven deep networks have demonstrated remarkable detection performance for infrared small targets. However, continuously increasing the depth of neural networks to enhance performance has proven impractical. Consequently, the i...
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