YOLO YOLOv8 AI technology Top Builders

Explore the top contributors showcasing the highest number of YOLO YOLOv8 AI technology app submissions within our community.

YOLO v8

Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.

What's new in YOLOv8?

YOLOv8 supports a full range of vision AI tasks, including detection, segmentation, pose estimation, tracking, and classification. This versatility allows users to leverage YOLOv8's capabilities across diverse applications and domains.

General
Relese date	May, 2023
Repository	https://github.com/ultralytics/ultralytics
Type	Real time object detection

Libraries

Discover YOLOv8

Documentation YOLOv8:
Quickstart Quickstart with YOLOv8
GitHub Repository View the GitHub repository for YOLOv8
Hugging Face Spaces Test YOLOv8 in the browser with Hugging Face Spaces

Edit on Github

YOLO YOLOv8 AI technology Hackathon projects

Discover innovative solutions crafted with YOLO YOLOv8 AI technology, developed by our community members during our engaging hackathons.

Smart Traffic

SmartTraffic operates on the innovative concept of dynamically adjusting traffic light signals based on the density of vehicles on the road. By intelligently monitoring traffic flow and adapting signal timings accordingly, the system aims to optimize the efficiency of urban transportation networks. When there are fewer vehicles on the road, SmartTraffic strategically switches traffic lights to green, capitalizing on the lower probability of congestion and minimizing the likelihood of traffic jams. This proactive approach not only helps to keep traffic moving smoothly but also contributes to reducing overall travel times and enhancing the overall driving experience for commuters. Through its ability to respond in real-time to changing traffic conditions, SmartTraffic represents a forward-thinking solution that holds great promise for creating more fluid and sustainable urban mobility systems in cognitive cities.

Pyropulse

Pyroplus presents a comprehensive solution to address the urgent challenges of wildfire management. Integrating IoT technology, AI algorithms, drones, and eco-friendly chemical materials, our system detects wildfires early using air quality sensors, analyzes data in real-time to guide response efforts, and employs drones for aerial surveillance and strategic firefighting. Our innovative chemical material, composed of cellulose, colloidal silica, sodium nitrite, and ammonium chloride, swiftly extinguishes fires while minimizing environmental impact. By combining cutting-edge technology with sustainable practices, Pyroplus aims to revolutionize wildfire management, protect ecosystems, and safeguard communities from the devastating effects of wildfires. Our LLM agent plays a pivotal role in enhancing public awareness and offering crucial instructions for fire protection. With a focus on preventing human-caused fires, which account for a staggering 95% of incidents, our agent acts as a proactive guide. Through informative content and clear directives, it empowers individuals with the knowledge needed to prevent wildfires, fostering a community-driven approach to fire safety.

SkyDoc

The problem SkyDoc solves Patchy Connectivity: Limited or unreliable internet access in rural areas. No Doctor Available: A scarcity of medical professionals accessible to rural patients. No Healthcare Facilities: Lack of local healthcare infrastructure or clinics. No Awareness + Basic Knowledge: Limited health awareness and basic medical knowledge among rural populations. Instant Healthcare Features: Voice and Video Call Appointments: Connects rural patients with doctors via video calls. Seamlessly transitions to voice calls in areas with poor network connectivity. Supports communication in local languages. Disease Prediction Using ML: Utilizes Machine Learning for early detection and prediction of diseases. Analyzes patterns and factors contributing to disease onset. Enables proactive healthcare management and personalized care plans. WhatsApp and SMS Diagnostics: Offers health updates and diagnostic information via SMS and WhatsApp. Ensures continuous communication between healthcare providers and patients. Includes details about health status and future appointments. Healthcare AI Assistant: A chatbot that provides 24/7 health-related information and advice. Powered by advanced AI for accurate and swift responses. Enhances decision-making and access to health information. Education Center: Features educational videos on a variety of healthcare topics. Offers practical demonstrations and expert-led content. Aims to increase health awareness and proactive management among users.

Saudi Swaift SAT

The persistent occurrence of oil spills in marine environments poses a significant threat to underwater ecosystems, necessitating a proactive approach for detection and mitigation. Traditional monitoring and response methods are often inefficient and lack precision, leading to prolonged environmental damage and loss of marine biodiversity. To address this pressing issue, there is a need for a sophisticated solution that integrates cutting-edge technology to enable early detection and rapid response to oil spills at sea. Leveraging CubeSat technology equipped with AI algorithms for real-time detection and blockchain technology for secure data transmission aims to establish a comprehensive system capable of effectively identifying oil spills as they occur, facilitating prompt intervention, and minimizing the ecological impact on marine life and resources. The proposed solution aligns with UN Sustainable Development Goal 14: Life Below Water. By employing advanced technologies like CubeSat with AI algorithms and blockchain, the solution aims to achieve targets such as reducing marine pollution (Target 14.1), protecting marine ecosystems (Target 14.2), and addressing ocean acidification (Target 14.3). This approach responds to the urgent need to preserve marine life and biodiversity, driven by the devastating impact of oil spills on underwater environments.

Autilent

Autilent is a smart solution that is capable of automatically detecting high risk situations during driving and then helps eliminate them. A special device powered by autilent's proprietary AI algorithms is installed inside the cabin of the vehicle. This device has two cameras, driver facing and road facing. The video feed is analysed in realtime by our in-car processor and the system then detects potential accident-causing actions e.g distractions, drowsiness, mobile phone usage etc. Realtime alerts are then generated to warn the drivers and alert the command and control centres in order to take preventative action. Additionally, we also offer data driven insights into every individual driver's behaviour and give hyper-personalised recommendations in order to bring a positive change in the driver behaviour and make them safer on the roads. We are on a mission to save lives and resources and look forward to your support in this. In the demo, please select the dates 1-15th March, and the driver: Saad Farooq, and in the vehicle section, KSA-006

World need talents

This project is an advanced platform that utilizes artificial intelligence to analyze football. The main goal of the platform consists of three main parts: Performance Analysis: The platform gathers data and statistics about players' performance in live matches. This is done using artificial intelligence techniques to analyze players' movements and estimate their positions on the field. This data is analyzed to identify each player's strengths and weaknesses, and how they can improve their performance. Talent Discovery: The platform uses artificial intelligence to discover young talents in football. Machine learning techniques are used to analyze players' performance in matches and training sessions, searching for performance patterns similar to professional players. Therefore, this project uses technology to make football more understandable and accessible, helping improve players' performance, uncover young talents, and make knowledge available to as many fans as possible. The main goal of this project is to use artificial intelligence for our understanding and analysis of football. By specifically analyzing the players' weight boxing statistics, lightweight boxing, strong and lightweight boxing for all players, they can improve them. In addition, the project aims to use artificial intelligence to transform young talents in football. This can help provide greater opportunities for talented young people who may be overlooked by the traditional screening system. Overall, the project aims to use technology to improve how feet are analyzed and understood, and to enable this knowledge to be accessible to as many people as possible