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Object Detection

Geospatial AI Services for Disaster Response and Management

Table of Contents How can geospatial AI improve disaster response? Geospatial AI revolutionizes disaster response and management by: Enhanced Situational Awareness: AI analyzes data from satellites, drones, sensors, and social media in real-time, giving responders a comprehensive view of the disaster area. Resource Optimization: Geospatial AI identifies optimal evacuation routes, supply distribution centers, and safe shelter locations.…

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Real-Time Object Tracking: Use Cases of Computer Vision Services

Table of Contents What industries use real-time object tracking? Real-time object tracking (RTOT) finds applications in various industries: Retail: Analyzing shopper behavior, optimizing product placement, heatmap generation. Manufacturing: Tracking product movement on assembly lines, quality inspection, inventory management. Security and Surveillance: Identifying suspicious activity, crowd monitoring, intrusion detection. Transportation: Traffic flow analysis, autonomous vehicle navigation, pedestrian safety. Healthcare: Patient monitoring,…

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Geospatial AI Services: Monitoring Environmental Changes and Climate Impact

Table of Contents What types of environmental changes can be monitored using geospatial AI? Geospatial AI provides powerful tools for monitoring a wide range of environmental changes: Deforestation: Detects changes in forest cover, identifies illegal logging, and analyzes the impact on biodiversity and carbon sinks. Land Use Change: Tracks urbanization, agricultural expansion, and wetland degradation, informing land…

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Precision Agriculture: Optimizing Crop Yields with Geospatial AI Services

Table of Contents How does geospatial AI specifically improve crop yields? Geospatial AI enhances crop yields in several fundamental ways: Targeted Interventions: AI analyzes field variability to tailor inputs (fertilizer, water, etc.) to specific crop needs, maximizing resource use. Early Problem Detection: AI identifies crop stress, disease or pest infestations early, enabling prompt and localized treatment.…

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How Computer Vision and Other Tech is Enabling the Next Generation of Smart Cities

How Computer Vision and Other Tech is Enabling the Next Generation of Smart Cities

A smart city is often described as a modern urban location that uses digital tools to automate systems and collect data to efficiently manage assets, resources and services to improve life for its inhabitants. The end result?  A city that operates more efficiently with fewer resources, increased levels of safety, reduced emissions and improved infrastructure. …

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Deep Learning for Satellite Imagery Blog

Satellite Image Classification with Deep Learning

In the past half-decade in Puerto Rico, we have had our fair share of catastrophic events such as hurricanes and earthquakes. These events have left significant parts of the population without power for extended periods of time, often ranging from days to weeks, or even months. As society becomes ever more connected and reliant on…

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Object Detection Models for Satellite Imagery

Salient Object Detection with Deep Learning

Increasing amounts of available satellite imagery has led to advances in the development of aerospace applications due to a wealth of information that needs to be analyzed. This has resulted in the growth of deep learning, an effective AI tool for object detection tasks and broad area search in satellite images. Wovenware’s data science team often…

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Anchor Boxes in Object Detection: When, Where and How to Propose Them for Deep Learning Apps

✕ Perhaps you’re well on your way to learning about computer vision and have studied in-depth, all about image classification and sliding window detectors. After grasping these concepts, the leap to understanding state-of-the-art (SOTA) object detection can often become daunting and obscure, especially when it comes to understanding anchor boxes. Needless to say, diving into a…

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