Abstract: Object Detection is an emerging ... of the last fully connected layer to target class probabilities, where each value ranges between 0 and 1. Analysis: I have implemented 4 datasets or ...

Abstract: The task of object detection is widely recognised as a prominent challenge ... The authors evaluate several novel models, such as Sparse R-CNN, Cascade R-CNN, Loss-Guided Attention RCNN, ...

An improved CNN for the anti-missile object detection algorithm based on improved attention mechanism ... idea of ECANet attention mechanism to improve and reorganize its pooling layer, and an ...

The goal of this research was to implement a multi-sensor–based fuzzy fusion algorithm to improve the robustness of any CNN-based object detection system ... VGG16 is a 16-layer CNN which introduced ...

Selective search algorithms are a basic phenomenon for object localization. In object detection after localization ... represents the architecture of the R-CNN and SPPNet. In SPPnet, it uses a maximum ...

Here I would like to discuss only the high-level intuition of Single Shot Multibox Detection ... CNN, we don’t only predict if there is an object in the image or not we also need to predict where in ...

Image recognition has made significant progress in recent years, majorly in the development of powerful algorithms ... fully connected layers that allow them to extract meaningful features from images ...