大模型与CoT经典论文阅读之——Zero-shot CoT, Manual CoT, AutoCoT ChatGPT 以及 GPT4 作为纯自回归式语言模型,本不应该期待其有什么推理能力,尤其是数学推理,但是他们在基础的推理任务上却十分让我们惊艳(当然肯定不能作为专业的数学解题工具),这让我们非常好奇… ...
git clone https://github.com/Applied-Deep-Learning-Lab/Yolov5_RK3588 And got into repo-dir: cd Yolov5_RK3588 Install RKNN-Toolkit2-Lite,such as rknn_toolkit_lite2-1.4.0-cp39-cp39-linux_aarch64.whl pip install install/rknn_toolkit_lite2-1.4.0-cp39-cp39-linux_aarch64.whl ...
由于在复杂的交互中,两臂与物体间会产生摩擦、粘附和变形,这些模型很难明确地构建出来,精确度也不是很高。一种有效的方法是模仿学习(imitation learning),即令专家为机器人提供期望行为的演示(输入状态和与状态对应目标动作的感知序列),机器人学习一个策略去模仿专家。另外,最近的深度模仿学习已经成功的只使用图像作为观...
CheSS: Chest X-Ray Pre-trained Model via Self-supervised Contrastive Learning Training deep learning models on medical images heavily depends on experts' expensive and laborious manual labels. In addition, these images, labels, and e... K Cho,KD Kim,Y Nam,... - 《Journal of Digital Imaging...
Explore Generative Adversarial Networks directly in the browser with GAN Lab. There are many cool features that support interactive experimentation. Interactive hyperparameter adjustment User-defined data distribution Slow-motion mode Manual step-by-step execution ...
Exploiting sequence–structure–function relationships in biotechnology requires improved methods for aligning proteins that have low sequence similarity to previously annotated proteins. We develop two deep learning methods to address this gap, TM-Vec a
We trained a ResNet101 deep learning model for image segmentation and zebrafish embryo detection with a positive predictive value of 99%. Application of this model to our experimental dataset combined with manual quality control facilitated segmentation into more than three million embryo image ...
Our process is scalable and requires minimum manual annotation effort. We mine bookmarks in our institute to develop DeepLesion, a dataset with 32,735 lesions in 32,120 CT slices from 10,594 studies of 4,427 unique patients. There are a variety of lesion types in this dataset, such as ...
Chapter18 Chapter19 Chapter2 Chapter20 Chapter3 Chapter4 Chapter5 Chapter6 Chapter7 Chapter8 Chapter9 docs scripts .gitignore Makefile README.md acknowledgments.tex acknowledgments_github.md applied_math_and_machine_learning_basics.tex breakcites.sty ...
(MoCo, v2)58,59, which leverages self-supervised learning to produce a pretrained feature extractor. In this process, the feature extractor is trained on a large dataset of fundus images without the need for manual annotations. MoCo v2 uses a momentum-based contrastive learning framework, where ...