Faster RCNN Architecture . The examples (train_v1.py, train_v2.py) use a Faster RCNN with a pretrained Resnet50 as a backbone.The model detects objects, masks and bounding boxes. Since the training ...

Model Architecture: Define the CNN-based model for object detection. Use layers such as convolutional, activation (ReLU), and fully connected layers. Implement object detection-specific outputs ...

Previous NAS focus on image classification, so directly implementing traditional NAS, like the last research work DetNet, on object detection tasks are ineffective. In general, conventional NAS only ...

In this work, we propose a digital accelerator architecture for a high-throughput, robust, scalable, and tunable visual object detection pipeline based on Histogram of Oriented Gradients (HOG) ...

The MOD-TD architecture, incorporating knowledge distillation, integrates advanced Transformer technology with CNN features to enhance object detection accuracy and robustness. It features an ...

With an objective of evaluating accuracy for real-time logo detection from video, the results are applicable on a logo image dataset suitable for detecting the classification accuracy of the logos. 1.

TOKYO, May 19, 2025 /PRNewswire/ -- Synspective Inc., a provider of Synthetic Aperture Radar (SAR) satellite data and analytics solutions, is pleased to announce the launch of its Object Detection ...

- Revolutionizing Vessels and Aircraft Monitoring with SAR Analytics - TOKYO, May 19, 2025 /PRNewswire/ -- Synspective Inc., a provider of Synthetic Aperture Radar (SAR) satellite data and analytics ...