@article{xie2023prompt,
            title={A Prompt Log Analysis of Text-to-Image Generation Systems},
            author={Xie, Yutong and Pan, Zhaoying and Ma, Jinge and Luo, Jie and Mei, Qiaozhu},
            journal={arXiv preprint arXiv:2303.04587},
            year={2023}
          }
}

@article{ma2022face,
        title={Face Animation with Multiple Source Images},
        author={Ma, Jinge and Pan, Zhaoying},
        journal={arXiv preprint arXiv:2212.00256},
        year={2022}
}

@article{ma2018holo,
        title={Realization Scheme for Visual Cryptography with Computer-generated Holograms},
        author={Yu, Tao, Ma, Jinge and Li,  Guilin et al.},
        journal={International Workshop on Holography and related technologies},
        year={2018}
}

• Back to 2019, CNN-based object detection algorithms utilize the Intersection-over-Union (IoU) metric to determine the allocation of anchors to objects. However, this method has certain limitations. To address this issue, we propose a new training approach called FreeAnchor, which allows for the free allocation of anchors.
• The main goal of FreeAnchor is to learn the most effective features for classification and object location. It can be used in conjunction with any CNN-based detection method, including Single Shot Detector (SSD).
• By incorporating FreeAnchor, we are able to improve the accuracy and speed of SSD, resulting in a detector that outperforms traditional single-stage methods, particularly in regards to slender, non-central, and densely-placed objects.

• I reviewed object detection algorithms, including Faster-RCNN, YOLO v3, and YOLO v4.
• I implemented YOLO v3 with PyTorch on the DOTA dataset to detect objects in remote sensing images. The image shows one example of object detection on remote sensing images and two zoomed-in parts of the example.

• I implemented simple CNN and LSTM with PyTorch and TensorFlow.
• I Implemented show and tell algorithm on UCM dataset with TensorFlow. The image shows two examples of image captioning on remote sensing images.

• I studied High-speed interface (JESD204B) and network LTE protocols.
• I researched and developed video compression algorithm based on JPEG XS.
• I investigated physical layer signal synchronization, frequency offset estimation, and compensation.
• I developed the low-latency I2S controller on FPGA.

• I worked as the team leader to complete the design and implementation of the portable electrocardiograph.
• We implemented the circuit and PCB design, PCB projection and welding, Matlab simulation of signal processing, FPGA-based signal processing, FPGA and WeChat applet-based Bluetooth communication, applet display, and functional interface development as a group.
• I worked on circuit design, Matlab simulation signal processing, FPGA-based signal processing, and Bluetooth communication.