Zhenduo Zhai
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View article: New Methods for Waterfowl and Habitat Survey Using AI and Drone Imagery
New Methods for Waterfowl and Habitat Survey Using AI and Drone Imagery Open
Monitoring waterfowl populations is essential for informing habitat management, conservation strategies, and sustainable harvest regulations. Many target species such as mallards and northern pintails are keystone components of wetland eco…
View article: Deep Learning Models for Waterfowl Detection and Classification in Aerial Images
Deep Learning Models for Waterfowl Detection and Classification in Aerial Images Open
Waterfowl populations monitoring is essential for wetland conservation. Lately, deep learning techniques have shown promising advancements in detecting waterfowl in aerial images. In this paper, we present performance evaluation of several…
View article: Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys
Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys Open
Unoccupied aerial systems (UASs) may provide cheaper, safer, and more accurate and precise alternatives to traditional waterfowl survey techniques while also reducing disturbance to waterfowl. We evaluated availability and perception bias …
View article: Temporal-Rate Encoding to Realize Unary Positional Representation in Spiking Neural Systems
Temporal-Rate Encoding to Realize Unary Positional Representation in Spiking Neural Systems Open
Unary representation is straightforward, error tolerant and requires simple logic while its latency is a concern. On the other hand, positional representation (like binary) is compact and requires less space, but it is sensitive to errors.…