Abstract: Monocular 3D object detection has gained considerable attention because of its cost-effectiveness and practical applicability, particularly in autonomous driving and robotics. Most of ...
Abstract: Small object detection in UAV aerial imagery presents significant challenges due to limited pixel coverage and complex backgrounds. This paper introduces DPLR-DETR (Dynamic Position Large ...
Subsistence farming plays a crucial role in the South African economic sector, supporting around 60 % of households [1]. However, food insecurity persists due to severe and unpredictable climate ...
Abstract: The challenge in open-world object detection, similarly to few- and zero-shot learning, is to generalize beyond the class distribution of the training data. In this paper, we propose a ...
Abstract: Millimeter-wave (mmWave) radars are increasingly popular in automotive, healthcare, civilian, and military applications due to their ability to operate in all weather conditions and provide ...
Abstract: Event cameras offer high temporal resolution and dynamic range with minimal motion blur, making them promising for robust object detection. While Spiking Neural Networks (SNNs) on ...
Abstract: Object detection is a fundamental computer vision task that simultaneously locates and categorizes objects in images and videos. It is utilized in various fields, such as autonomous driving, ...
face-mask-detection/ ├── dataset/ │ ├── with_mask/ # Training images with masks │ └── without_mask/ # Training images without masks ├── model/ │ ├── mask_detector.h5 # Trained model (generated) │ └── ...
Abstract: In recent years, Object detection and tracking has emerged as a key enabler for intelligent automation in the application domains including surveillance, autonomous driving, smart farming, ...
Abstract: The identifying of brain tumor is one of the most important elements of the whole process of medical diagnosis nowadays and the result must be very accurate and explainable so that the ...
Abstract: Anemia is a global health concern impacting vulnerable populations which necessitates improved diagnostic methods beyond traditional approaches such as complete blood count. This study ...