Object detection on fused images of visible and infrared modals is great importance for many applications, example, surveillance rescue at low-light conditions. However, current detectors have difficulty robust image mainly two reasons. First, objects are presented in various shapes sizes, making some hard samples cannot be localized accurately. Second, the same object category will different a...

Cell tracking and motility analysis are essential for understanding multicellular processes, automated quantification in biomedical experiments, medical diagnosis treatment. However, manual is labor-intensive, tedious, prone to selection bias errors. Building upon our previous work, we propose a new deep learning-based method, EDNet, cell detection, tracking, that more robust shape across diffe...

The detection of grain pests is great significance to storage. However, in practice, because the size insects too small identify. In this paper, feature fusion SSD(single shot multi-box detector) algorithm based on Top-Down strategy was proposed. Firstly, module used fuse output characteristics conv4 and conv5, block 11 which not conducive object deleted. Secondly, K-means clustering cluster pr...

Object search is a challenging yet important task. Many efforts have been made to address this issue and achieve great progress in natural image, searching all specified types of objects from remote sensing image barely studied. In work, we are interested images. Compared person scenes, task two factors: One that usually contains large number objects, which poses challenge characterize the obje...

Lucy Y. Pao Northwestern University Evanston, IL 60208 Abstract There have been several algorithms proposed for multisensor tracking of multiple objects using a centralized processing architecture, but because of considerations such as reliability, survivability, and communication bandwidth, distributed processing architectures are often the only alternative. The distributed fusion problem is m...