arXiv ·
Researchers are exploring computer vision models to mitigate Camel-Vehicle Collisions (CVC) in Saudi Arabia, which have a high fatality rate. They tested CenterNet, EfficientDet, Faster R-CNN, and SSD for camel detection, finding CenterNet to be the most accurate and efficient. Future work involves developing a comprehensive system to enhance road safety in rural areas.
arXiv ·
Researchers in Saudi Arabia are applying computer vision techniques to reduce Camel-Vehicle Collisions (CVCs). They tested object detection models including CenterNet, EfficientDet, Faster R-CNN, SSD, and YOLOv8 on the task, finding YOLOv8 to be the most accurate and efficient. Future work will focus on developing a system to improve road safety in rural areas.
KAUST ·
A KAUST-led study identified 15 large mammal species that inhabited the Arabian Peninsula in the last 10,000 years, tripling previous estimates. Researchers analyzed thousands of petroglyphs from scientific expeditions, publications, and social media. The study identified two species never known to live in the region before: the greater kudu and the Somali wild ass. Why it matters: The findings provide a benchmark for rewilding efforts and inform decisions on which mammals to reintroduce to the region.
arXiv ·
The paper introduces a framework for camel farm monitoring using a combination of automated annotation and fine-tune distillation. The Unified Auto-Annotation framework uses GroundingDINO and SAM to automatically annotate surveillance video data. The Fine-Tune Distillation framework then fine-tunes student models like YOLOv8, transferring knowledge from a larger teacher model, using data from Al-Marmoom Camel Farm in Dubai.
arXiv ·
Researchers at KFUPM have developed a system for pothole detection and characterization using a YOLOv8-seg model and depth estimation. A new dataset of images and depth maps was collected from roads in Al-Khobar, Saudi Arabia. The system combines segmentation and depth data to provide a more comprehensive pothole characterization, enhancing autonomous vehicle navigation and road maintenance.
KAUST ·
A group of KAUST students visited the National Wildlife Research Center (NWRC) in Taif as part of the University's 2015 Winter Enrichment Program. The NWRC, established in 1986, focuses on preserving and reintroducing species like the houbara bustard, Arabian oryx, red-necked ostrich, and Arabian leopard. Researchers at the center track released bustards via radio transmitters, collaborating internationally to preserve their habitats. Why it matters: This highlights Saudi Arabia's commitment to wildlife conservation and international collaboration in ecological research, showcasing KAUST's engagement with regional environmental initiatives.
arXiv ·
The paper introduces VENOM, a text-driven framework for generating high-quality unrestricted adversarial examples using diffusion models. VENOM unifies image content generation and adversarial synthesis into a single reverse diffusion process, enhancing both attack success rate and image quality. The framework incorporates an adaptive adversarial guidance strategy with momentum to ensure the generated adversarial examples align with the distribution of natural images.