Deep Learning (DL) has been described as one of the key subfields of Artificial Intelligence
(AI) that is transforming weed detection for site-specific weed management (SSWM). In the …

Data transmission accounts for significant energy consumption in wireless sensor networks
where streaming data is generated by the sensors. This impedes their use in many settings …

Visual sensing of the environment is crucial for flying an unmanned aerial vehicle (UAV) and
is a centerpiece of many related applications. The ability to run computer vision and …

Deep learning-based object detection algorithms have been widely used and are effective in
autonomous driving. But their performance degrades dramatically under low-light …

Several recent works seek to create lightweight deep networks for video object detection on
mobiles. We observe that many existing detectors, previously deemed computationally …

Given the global biodiversity crisis, there is an urgent need for new tools to monitor
populations of endangered marine megafauna, like sharks. To this end, Baited Remote …

Efficient and adaptive computer vision systems have been proposed to make computer
vision tasks, such as image classification and object detection, optimized for embedded or …

Efficient and adaptive computer vision systems have been proposed to make computer
vision tasks, such as image classification and object detection, optimized for embedded or …

Resource-constrained electronic systems are present in many semi-and fully-autonomous
systems and are tasked with computationally heavy tasks such as neural network image …

Mobile devices such as drones and autonomous vehicles increasingly rely on object
detection (OD) through deep neural networks (DNNs) to perform critical tasks such as …