You can retrieve moments of interest from the long-term untrimmed video in just a few simple steps. Notably, this system possesses zero-shot capabilities, allowing it to quickly adapt to new open-set video content. It is beneficial for various valuable downstream tasks, such as content monitoring and auditing, video summarization and clipping, video search engines, creating video-text pair datasets, and AD placement.

This challenge included four tasks: autonomous grasping and placing, dual-arm coordinated assembly, dual-arm coordinated construction, and dual-arm coordinated transportation. The competition was held within a designated workspace, using dual-arm collaboration to complete complex tasks. It simulated scenarios where robots perform part assembly and transportation.

It is implemented using cross-compilation with C++ and Python in QT5. It enables rapid data augmentation of batch image datasets, including color enhancement, brightness adjustment, scale transformation, affine transformation, and angle transformation. Additionally, it supports automatic annotation and validation of the augmented image data. It significantly shortens the initial dataset creation process.

Automated patch clamp technology can independently execute experimental operations according to the experimental plan. It requires operating on cells within a highly limited space. By integrating the laboratory's existing microscopy system, a four-axis micromanipulator that meets experimental needs was designed and subjected to simulation analysis. The simulation analysis revealed that the optimal approach angles for the micromanipulator under 40x0.8, 25x1.0, and 25x0.95 objectives were 27°, 29°, and 29°, respectively.