The study aims to explore a method for identifying corresponding objects across multiple camera views, to improve the accuracy of object re-identification. We analyzed various techniques, including contour detection, region of interest extraction, and keypoint extraction. We also examined the challenges of finding object correspondences between multiple camera views. To evaluate the effectiveness of the proposed method, we utilized two human attribute datasets, Market-1501 and DukeMTMC-reID, and performed extensive testing on these datasets.
Nowadays, speech-processing technologies with different language systems are successfully used in mobile and stationary devices. Kazakh is considered a low-resource language, which poses various challenges for conventional speech recognition methods. This paper presents a proposed model capable of multitasking and handling concurrent speech recognition, dialect identification, and speaker identification, all in an end-to-end framework. The developed multitask model enables training three different tasks within a single model. A multitask recognition system is created based on the WaveNet-CTC model. Experiments show that for the concrete task end-to-end multitask model has better performance than other models.
This paper studies the feasibility of reciprocating motion of non-contact control implants (small permanent magnets) by simulating a magnetic stereotaxic system using COMSOL software. The experimental results are consistent with the simulation results. When the large permanent magnet (LPM) on one side is approached, it will attract the small permanent magnet (SPM) to move towards the barrel wall, and when it leaves, the small permanent magnet stays at the barrel wall. At this time, the large permanent magnet on the other side begins to approach. When a certain distance is reached, the small permanent magnet is attracted by it, moves from one side of the barrel wall to the other side, and stays on the barrel wall after arrival.
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