Object detectionAtrous convolutionFeature fusionDetecting small objects is a challenging job for the single-shot multibox detector (SSD) model due to the limited information contained in features and complex background interference. Here, we increased the performance of the SSD for detecting target ...
Detecting small objects is a challenging job for the single-shot multibox detector (SSD) model due to the limited information contained in features and com
论文：LA-YOLO: Bidirectional Adaptive Feature Fusion Approach for Small Object Detection of Insulator ...
Because of SSD predicting small objects with its shallower layers,所以我们不用对应大目标的 deeper layers For choosing the proper feature fusion layers, effective receptive fields in different layers are explored with deconvolution method 对应上图中的小船,SSD中的 conv4_3 对应的 effective receptive fiel...
FFN可以提高提出的模型对整个目标部分的关注,从而实现更准确的小目标检测。 图3为DOTA上平均定位误差及与背景混淆的曲线图。与其他模型相比,IPSSD具有更好的性能。 4、参考 [1].ENHANCED SINGLE-SHOT DETECTOR FOR SMALL OBJECT DETECTION IN REMOTE SENSING IMAGES....
但SSD 也有一个痛点——它对小目标的检测能力较弱。这就像是戴着一副老花镜去看远方的蚂蚁,模糊不清。DSSD(Deconvolutional Single Shot Detector)就是为了解决这个问题而生的。它的核心改进点在于引入了反卷积(Deconvolution)层,增强了小目标的检测能力。
能够提升对小物体的置信Perceptual Generative Adversarial Networks for Small Object Detection (用于小目标...
Once the detector is trained and evaluated, you can generate code for thessdObjectDetectorusing GPU Coder™. For more details, seeCode Generation for Object Detection by Using Single Shot Multibox Detectorexample. Supporting Functions functionB = augmentData(A)% Apply random horizontal flipping, ...
small convolutional filter to predict object categories and offsets in bounding box locations, using separate predictors (filters) for different aspect ratio detections, and applying these filters to multiple feature maps from the later stages of a network in order to perform detection at multiple ...
concatenation=pooling+deconvolution,这样每一个尺度的特征图数量都是一样的,这就导致后面可以使用一个分类器在不同尺度上检测 By using a single classifier, improvement on the generalization performance can be expected, and it can be effectively used for datasets with size imbalance or for small datasets....