Deep network pruning for object detection
WebNov 6, 2024 · As deep learning has demonstrated remarkable performance in recent years, researchers have proposed various applications in the field of intelligent networked vehicles and drones, including video surveillance, object tracking, autonomous driving, and robot vision. Among these applications, object detection always plays an important role. WebTridentNet：Scale-Aware Trident Networks for Object Detection. arxiv 2024 PDF 处理目标检测中尺度变化新思路 Dilated convolution has now been widely used in object detection, and proves to be effective for improved accuracy without any additional parameters and computational cost.
Deep network pruning for object detection
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WebAug 25, 2024 · 3.3. Localization-aware channel pruning. After we construct the auxiliary network and the localization-aware loss, we can conduct channel pruning with them layer by layer. The pruning process of the whole model is described in Algorithm 1. For better description of the channel selection algorithm, some notations are given first. WebOct 25, 2024 · aerial object detection; convolutional neural networks; deep compression; network pruning 1. Introduction Aerial target detection is an important computer vision technology that has been widely used in many fields (such as crop monitoring, resource exploration, and environmental protection).
Webworks, i.e., a deep network to prune another deep network, it is different from student-teacher based knowledge distilla-tion approaches [16] to deep model compression where the idea is to compress a teacher network into a simpler student network. In contrast, our approach learns a deep multitask network that prunes a target network. 2 ... WebMar 1, 2024 · Channel pruning is one of the important methods for deep model compression. Most of existing pruning methods mainly focus on classification. Few of them conduct systematic research on...
WebDec 29, 2024 · This study details the development of a lightweight and high performance model, targeting real-time object detection. Several designed features were integrated into the proposed framework to accomplish a light weight, rapid execution, and optimal performance in object detection. Foremost, a sparse and lightweight structure was … WebJul 30, 2024 · Pruning Deep Neural Networks [Lecun et al. NIPS’89] [Han et al. NIPS’15] Networks generally look like the one on the left: every neuron in the layer below has a connection to the layer above, but this …
WebNov 1, 2024 · Channel pruning is one of the important methods for deep model compression. Most of existing pruning methods mainly focus on classification. Few of them conduct systematic research on object detection. However, object detection is different from classification, which requires not only semantic information but also localization …
WebApr 8, 2024 · Under object detection and segmentation tasks, SLR also converges $2\times$ faster to the desired accuracy. Further, our SLR achieves high model accuracy … nutrition facts blank templateWebAbstract: Deep Neural Networks (DNNs) in general and Convolutional Neural Networks (CNNs) in particular are state-of-the-art in numerous computer vision tasks such as object classification and detection. However, the large amount of parameters they contain leads to a high computational complexity and strongly limits their usability in budget-constrained … nutrition facts beyond burgerWebOct 7, 2024 · Moreover, pruning some object detection models lead to a moderate drop in performance (mAP) [7, 36 ... Deep neural networks (DNNs) have largely boosted their performances on many concrete tasks ... nutrition facts black teaWebApr 6, 2024 · The proposed method can effectively embed the DNN-based object detector into an edge device equipped with Qualcomm’s QCS605 System-on-Chip (SoC), while … nutrition facts blow popWebSep 1, 2024 · To prune the deep models for object detection, Ghosh et al. [31] analyzed the pruning approach about the detection networks and utilized the pruning technique … nutrition facts blankWebApr 6, 2024 · The proposed method can effectively embed the DNN-based object detector into an edge device equipped with Qualcomm’s QCS605 System-on-Chip (SoC), while achieving a real-time operation with more than 10 frames per second. This paper presents a method for simplifying and quantizing a deep neural network (DNN)-based object … nutrition facts body armor lyteWebMar 3, 2024 · It will find the best way to prune (Best threshold) all the parameters from 40%. Hence different tensors may have different compression ratios at the end. But eventually, the entire network will be prune from 40%. If we print the state dictionary of the model after running those lines, we can see an output like this. nutrition facts breast meat turkey