The identification of pavement cracks is critical for ensuring road safety. Currently, manual crack detection quite time-consuming. To address this issue, automated crack-detecting technology required. However, automatic recognition remains challenging, owing to the intensity heterogeneity and complexity backdrop, e.g., low contrast damages backdrop may have shadows with comparable intensity. M...

Road detection technology plays an essential role in a variety of applications, such as urban planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there has been much development detecting roads high-resolution (HR) satellite images based on semantic segmentation. However, the objects being segmented are small size, not all information is equally important when...

A pothole is an open crack developed on roads owing to varied climatic situations and exposure heavy-load trucks. Potholes are acting as one of the major causes accidents economic loss in repair vehicles. Hence this paper proposes a detection system that assists drivers avoiding potholes road by providing prior warnings using YOLOV7 machine learning technique. The warning can be like buzzer whi...

K-complex is an underlying pattern in the sleep EEG. Due to the role of sleep studies inneurophysiologic and cognitive disorders diagnosis, reliable methods for analysis and detection of this patternare of great importance. In our previous work, Synchrosqueezing Transform (SST) was proposed for analysisof this pattern. SST is an EMD-like tool, which benefits from wavelet transform and reallocat...

We consider the problems of sequential prediction and change detection that arise often in interactive applications: A semi-automatic predictor is applied to a time-series and is expected to make proper predictions and request new human input when change points are detected. Motivated by the Transductive Support Vector Machines (Vapnik 1998), we propose an online framework that naturally addres...

We consider the problem of spatial-temporal modeling of interactive image interpretation. The interactive process is composed of a sequential prediction step and a change detection step. Combining the two steps leads to a semi-automatic predictor that can be applied to a time-series, yields good predictions, and requests new human input when a change point is detected. The model can effectively...

T his paper discusses the main architectural issues of a challenging application of real-time image processing: the vision-based automatic guidance of road vehicles. Two algorithms for lane detection and obstacle localization, currently implemented on the ARGO autonomous vehicle developed at the University of Parma, are used as examples to compare two di€erent computing engines Ð a massively pa...

premature ventricular contraction (pvc) is one of the common cardiac arrhythmias. the occurrence of pvc is dangerous in people who have recently undergone heart. a pvc beat can easily be diagnosed by a doctor based on the shape of the electrocardiogram signal. but in automatic detection, extracting several important features from each beat is required. in this paper, a method for automatic dete...

Aiming at the problem of automatic identification and evaluation of road damage degree, the road damage identification and degree assessment algorithms based on unmanned vehicles experimental platform are studied. The road crack segmentation extraction method based on adaptive sliding window is studied. On this basis, the road damage crack classifies and identifies according to the crack geomet...

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we intr...