5 accepted papers
4D radar-based object detection has garnered great attention for its robustness in adverse weather conditions and capacity to deliver rich spatial information across diverse driving scenarios. Nevertheless, the sparse and noisy nature of 4D radar point clouds poses substantial challenges for effecti
Most existing change detection (CD) methods focus on spatial domain modeling, while ignore the rich information of frequency domain. In this paper, we enhance the feature representative ability with spatial and frequency feature cross enhancement. Specifically, we propose a Change Feature Extract Mo…
Multiscale convolutional neural network (CNN) has demonstrated remarkable capabilities in solving various vision problems. However, fusing features of different scales always results in large model sizes, impeding the application of multiscale CNNs in RGB-D saliency detection. In this paper, we prop…
Semi-supervised change detection (SSCD) utilizes partially labeled data and a large amount of unlabeled data to detect changes. However, the transformer-based SSCD network does not perform as well as the convolution-based SSCD network due to the lack of labeled data. To overcome this limitation, we…
Active suspensions are important features of many recent planetary rovers. For such a rover, the control strategy is crucial to its performance. This letter presents the control method for a planetary rover equipped with an active suspension system. The control algorithm is based on the estimation o