8 accepted papers
Unsupervised cross-modal hashing has gained significant attention for efficient retrieval between heterogeneous modalities through encoding data into the unified binary representations, offering low storage cost and fast response. However, the constraints of existing methods persist in bridging the
Magnetic soft robots have shown great potential in various applications, including targeted delivery and therapy. However, current magnetic soft robots lack sufficient intelligence for autonomous decision-making, limiting their ability to adapt to dynamic and unstructured environments. To address th
Hashing has been widely applied in large-scale multimodal retrieval by mapping heterogeneous modalities data into binary codes. However, most cross-modal hashing methods cannot make the most of semantic information to construct the association relations of sample pairs, resulting in unsatisfactory r…
The first author's name was misspelled as “Chengyao Tian” in [1], containing an extraneous “g”. The correct spelling is “Chenyao Tian”.
Unsupervised deep cross-modal hash retrieval aims to map multi-modal features into binary hash codes without labels, which is of interest due to its storage efficiency, query speed and convenient applications. However, existing approaches suffer from two main limitations: (1) Slightly insufficient c…
Unsupervised cross-modal hashing methods have become a core technology for retrieving vast amounts of heterogeneous multimedia information due to their advantages in retrieval speed and storage efficiency. Although these methods have made significant progress in the field of multimedia retrieval, th…
Action segmentation plays an important role in video understanding, which is implemented by frame-wise action classification. Recent works on action segmentation capture long-term dependencies by increasing temporal convolution layers in Temporal Convolution Networks (TCNs). However, high layers in…
It is of great importance to pick up a single carbon nanotube (CNT) from a bulk of CNTs for nanodevice fabrication. In this study, we have proposed a nanorobotic manipulation system allowing automated pick-up of CNTs based on visual feedback. We utilize histogram normalization for automatic binariza…