deep learningYOLOv4 algorithmdata transmissionvehicle detectionFor a majority of remote sensing applications of unmanned aerial vehicles (UAVs), the data need to be downloaded to ground devices for processing, but this procedure cannot satisfy the demands of real-time target detection. Our objective ...
To be specific, Faster-R-CNN is an excellent two-stage method for target detection, while YOLO and SSD are one-stage schemes and are more time-friendly. Target detection methods based on deep learning for RSIs can be further categorized into two groups: one based on deep belief networks (...
2. 同时输入的目标真实状态,可以生成一个预测值和真实值之间的残差值,更便于网络进行学习。 3.2The DeepMTT network DeepMTT 网络由3个双向LSTM层、1个滤波层、1个最大池化层和1个线性输出层组成。输入\hat{\bf{x}}_{1:K}^N,输出为预测的残差值{\bf{r}}_{1:K}。网络结构图如下所示。 DeepMTT 网络...
As a classic subject in the field of image processing and computer vision, target detection has a wide range of applications in traffic monitoring, image retrieval, human-computer interaction and so on. It aims at detecting objects of interest in a static image. In view of the strong expressiv...
传统的方式往往依赖于药物和靶标的描述符。在我们的工作中,开发了DeepDPIs(一个基于深度学习的工作流程),来预测DTIs。首先,通过无监督预训练抽取描述符表征,然后通过已知的相互作用对构建分类模型。与已知表现较好的现有方法相比,DeepDPIs表现更好。 Flowchart Figure 2...
这种方法也常被称为tracking-by-detection。近年来,各种机器学习算法被应用在判别式方法上,其中比较有代表性的有多示例学习方法(multiple instance learning), boosting和结构SVM(structured SVM)等。判别式方法因为显著区分背景和前景的信息,表现更为鲁棒,逐渐在目标跟踪领域占据主流地位。值得一提的是,目前大部分深度...
"""Deep Q Learning:支持离散/连续状态&动作空间,无需 target network 实现稳定高效学习作者: Surfer Zen @https://www.zhihu.com/people/surfer-zenURL: https://zhuanlan.zhihu.com/p/6760622732024 年 01 月注:1. 本代码遵循 MIT 开源协议2. 仅供学习使用,如需在学术论文中使用本代码或本文观点,请进行合...
ValueError: Using a target size (torch.Size([1])) that is different to the input size (torch.Size([169])) is deprecated. Please ensure they have the same size. Pneumonia heart disease dataset I have used. code Training the DCGANs criterion = nn.BCELoss() # We ...
I understand Q-learning. Q-learning is value-based reinforcement learning algorithm that learns “optimal” probability distribution between state-action that will maximize it’s long term discounted reward over a sequence of timesteps. The Q-learning is updated using the bellman equation, and a si...
在这过程中会出现一些多目标跟踪中常见的问题,这些问题主要是针对视频中存在的具有不同光照,不同水平的遮挡情况,不同的视点的大量的data present进行建模。Tracking-by-detection这种策略是目前解决这些问题最为成功的了。 The task is then to associate each measurement to a corresponding target to address the pr...