As we know, image classification is probably the most common use for deep neural network in computer vision. Most of the CNN networks are designed to extract features from images which can be later used to recognize it. This lead to an intuitive strategy for object detection: the region based...
The widely used object detection applications are human鈥揷omputer interaction, video surveillance, satellite imagery, transport system, and activity recognition. In the wider family of deep learning architectures, convolutional neural network (CNN) made up with set of neural network layers is used ...
Perform classification, object detection, transfer learning using convolutional neural networks (CNNs, or ConvNets), create customized detectors
MSCNN论文解读-A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection,程序员大本营,技术文章内容聚合第一站。
CNN(convolutional neural network)在目标检测中大放异彩,R-CNN系列,YOLO,SSD各类优秀的方法层出不穷。在2D图像的目标检测上,不少学术界提出的框架已经投入商用。但是,具体落实到自动驾驶、机器人这类应用场景上时,2D场景下的目标检测对于3D真实世界的场景描述依然不够。
图像分类优化技巧(Bag of Tricks for Image Classification with Convolutional Neural Networks) Bag of Freebies for Training Object Detection Neural Networks,李沐大神19年2月的新作,用卷积神经网络进行目标检测的一些技巧。 论文:Bag of Freebies for Training Object Detection Neural Networks ...
= rcnnObjectDetector with properties: Network: [11 Series] ClassNames: {'stopSign' 'Back'} RegionProposalFcn: @rcnnObjectDetector.proposeRegions References [1] Girshick, Ross, et al. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation...
Because a convolutional neural network (CNN) can process an input image in a convolutional manner, a spatial location in the input can be related to a spatial location in the output. This convolutional correspondence means that a CNN can extract image features for an entire image at once. The...
Convolutional predictors for detection 每一个添加的特征层(或者在基础网络结构中的特征层),可以使用一系列 convolutional filters,去产生一系列固定大小的 predictions,具体见 Fig.2。对于一个大小为m×n,具有p 通道的特征层,使用的 convolutional filters 就是3×3×p 的 kernels。产生的 predictions,那么就是归属...
because object detection performance of the convolutional neural network and a depth of the convolutional neural network are in a trade-off relationship, there are many attempts on a way to improve performance of object detection at the same time with simplifying an algorithm of the neural network...