The identification method of rice seedling rows based on machine vision is affected by environmental factors that decrease the accuracy and the robustness of the rice seedling row identification algorithm (e.g., ambient light transformation, similari...
Landslide susceptibility mapping (LSM) is significant for disaster prevention and mitigation, land use management, and as a reference for decision-making. Convolutional neural networks (CNNs) in deep learning have been successfully applied to LSM stu...
The ship detection task using optical remote sensing images is important for in maritime safety, port management and ship rescue. With the wide application of deep learning to remote sensing, a series of target detection algorithms, such as faster re...
Due to the complexity of airborne remote sensing scenes, strong background and noise interference, positive and negative sample imbalance, and multiple ship scales, ship detection is a critical and challenging task in remote sensing. This work propos...
Flying bird detection has recently attracted increasing attention in computer vision. However, compared to conventional object detection tasks, it is much more challenging to trap flying birds in infrared videos due to small target size, complex back...
This research proposes using a neural network to detect and identify the landmark points of the carapace of the Chinese mitten crab, with the aim of improving efficiency in observation, measurement, and statistics in breeding and sales. A 37-point lo...
In public safety scenarios, such as large-scale event security and urban crowd management, unmanned aerial vehicles (UAVs) serve as a vital tool for crowd localization, offering high mobility and broad coverage. However, UAV-based overhead localizati...
Tornado damage estimation is important for providing insights into tornado studies and assisting rapid disaster response. However, it is challenging to precisely estimate tornado damage because of the large volumes of perishable data. This study pres...
The problem of 3D human pose estimation (HPE) has been the focus of research in recent years, yet precise estimation remains an under-explored challenge. In this paper, the merits of both multiview images and wearable IMUs are combined to enhance the...
Radio interference in the uplink makes communication to satellites in the UHF amateur radio band (430–440 MHz) challenging for any satellite application. Interference measurements and characterisation can improve the robustness and reliability of the...
During cherry-tomato-bunch harvesting, clustered fruits, thin stems, and ambiguous fruit–stem junctions cause missed detections and errors in picking-point localization. To address these challenges, we propose TSP-Net, a structure-aware and geo...
Measured radar point-target detection under ground clutter is difficult because weak target echoes often compete with clutter peaks, and image-space detections do not directly represent physical range-Doppler coordinates. This paper proposes a wavefo...
Uterine cervical cancer is a leading cause of women’s mortality worldwide. Cervical tissue ablation is an effective surgical excision of high grade lesions that are determined to be precancerous. Our prior work on the Automated Visual Examination (AV...
The spatial distribution of gas emitted from an odor source provides valuable information regarding the composition, size, and localization of the odor source. Surface-enhanced Raman scattering (SERS) gas sensors exhibit ultra-high sensitivity, molec...
Autonomous driving has received enormous attention from the academic and industrial communities. However, achieving full driving autonomy is not a trivial task, because of the complex and dynamic driving environment. Perception ability is a tough cha...
Small fruits and partially occluded contours make strawberry instance segmentation difficult in greenhouse images. This study develops PMH-YOLO11-seg from YOLO11l-seg to examine whether finer spatial features and auxiliary localization supervision im...
Wideband signal detection and recognition (WSDR) is considered an effective technical means for monitoring and analyzing spectra. The mainstream technical route involves constructing time–frequency representations for wideband sampled signals a...
Accurate temperature control in ceramic roller kilns is critical for ensuring product quality; however, it remains challenging due to nonlinear thermal dynamics and the spatial lag inherent in traditional contact-based sensors. To address the limitat...
In millimeter-wave frequency-modulated continuous-wave (FMCW) multiple-input multiple-output synthetic-aperture radar (MIMO-SAR) imaging, platform displacement beyond the spatial Nyquist limit during a slow-time sampling interval creates aperture gap...
Accurate prediction of compost maturity is vital for ensuring quality, safety, minimum substrate weight loss and agronomic performance of compost products. In this study, eight supervised machine learning (ML) classification models including Random F...
Trade globalization is increasingly being reassessed through the lens of the green transition, as openness to international markets does not necessarily imply environmentally sustainable integration. The objective of this study was to assess whether...
Infrastructure 3D Object Detection is a pivotal component of Vehicle-Infrastructure Cooperated Autonomous Driving (VICAD). As turning objects account for a high proportion of traffic at intersections, anchor-free representation in the bird’s-ey...
The attitude determination accuracy of star sensors depends heavily on the precision of star centroid estimation. However, complex degradation scenarios—including low signal-to-noise ratio (SNR), intense stray light, and isolated hot pixels ind...
This paper investigates within-scene path loss prediction at 1.8 GHz in a smart-campus micro-urban environment using multivariate machine-learning (ML) models. We leverage an open measurement campaign from Covenant University (Nigeria) comprising thr...
Device-free fall detection using Wi-Fi Channel State Information (CSI) is promising for pervasive health monitoring but is impeded by environmental dependency and a high computational cost. While deep learning (DL) methods can automatically extract f...
This paper proposes a micro-Doppler flash detection framework for hovering unmanned aerial vehicle (UAV) detection with linear frequency modulated continuous wave (LFMCW) radar under the dual constraints of strong ground clutter and severe thermal no...
Object detection in remote sensing images (RSIs) suffers severely from small-scale instances, which are inherently constrained by extremely low pixel occupancy, fragile spatial detail retention, and insufficient discriminative feature representation....
River-training structures such as spur dikes are frequently used in the field of river engineering, which play a critical role in flow regulation and stabilization of the riverbank. However, previous studies lack a precise prediction of factors induc...
Cementitious sand and gravel (CSG) is commonly used in construction engineering; however, its mix proportion design is complex, and traditional physical experiments face limitations such as long cycles, high costs, and susceptibility to external fact...
Background: Mathematical models inspired by the Human Visual System (HVS) bridge the gap between biological perception and computer vision, by offering powerful frameworks for representing, enhancing, and analyzing digital images. From their initial...