We designed an architecture named Aristotle to execute neural networks for both object detection and semantic segmentation on FPGA. DNNDK (Deep Learning ...
We designed an architecture named Aristotle to execute neural networks for both object detection and semantic segmentation on. FPGA. DNNDK (Deep Learning ...
Thus, our FPGA system meets real-time processing requirements and has low power consumption, which means our system is highly suitable for embedded systems.
Deep learning models can automatically learn to represent data hierarchically, meaning that each layer in a neural network extracts increasingly abstract ...
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In this paper, we proposed a Highly Coupled Network (HCNet) for joint objection detection and semantic segmentation. ... object detection and semantic ...
Nov 1, 2022 · In this study, we design and implement real-time object detection and recognition systems using the single-shoot detector (SSD) algorithm and deep learning ...
Real-time Joint Object Detection and Semantic Segmentation Network for ...
ar5iv.labs.arxiv.org › abs
In this paper, we present a joint multi-task network design for learning object detection and semantic segmentation simultaneously. The main motivation is to ...
Sep 25, 2023 · Learn about image segmentation with deep learning and the most important datasets. Find the most popular applications of image segmentation.
In this review, we provide a comprehensive overview of the impact of deep learning on EO applications by reviewing 429 studies on image segmentation and object ...
This review paper starts with a quick overview of object detection followed by object detection frameworks, backbone convolutional neural network, and an ...