computer vision neural network deep MLP paradigm shift Introduction In computer vision, the ambition to create a system that imitates how the brain perceives and understands visual information fueled the initial development of neural networks.1,2 Subsequently, convolutional neural networks (CNNs),3, ...
许多后续研究工作都采用了基于单层LSTM的解码器,大多没有任何架构变化[50]、[51]、[67],而其他作品则提出了重大修改,总结如下。 视觉哨兵——Lu等人[43]用一个额外的可学习向量(称为Visual sentinel)增强了空间图像特征,当生成不需要视觉特征的“非视觉”单词(如“the”、“of”和“on”)时,解码器可以代替视觉...
A survey on different agricultural UAV types and their applications is presented in Sect. 3, while diverse UAV-based camera sensors used to detect crop and plant diseases are presented in Sect. 4. In Sect. 5, we present the effectiveness of different deep learning algorithms to identify crop ...
^B. Wu, C. Xu, X. Dai, A. Wan, P. Zhang, M. Tomizuka, K. Keutzer, and P. Vajda, “Visual transformers: Token-based image representation and processing for computer vision,” arXiv preprint arXiv:2006.03677, 2020. ^A. Srinivas, T.-Y. Lin, N. Parmar, J. Shlens, P. Abbeel, ...
1.1Previous survey The early review work (Sarafianos et al.2016) offers a taxonomy of methods depending on input types such as images or image sequences and single or multiple views scenarios. It covers both traditional and a few deep learning-based approaches. The study also introduces a nove...
A Survey of Visual Transformers Abstract Transformer是一种基于注意力的编码器-解码器架构,它彻底改变了自然语言处理领域。受这一重大成就的启发,近年来在将类似transformer的架构应用到计算机视觉(CV)领域方面进行了一些开创性的工作,这些工作已经证明了它们在各种CV任务中的有效性。凭借具有竞争力的建模能力,与现代卷...
2022 IJCV Deep Image Deblurring: A Survey 2022 WACV Deep Feature Prior Guided Face Deblurring 2022 CVPR Restormer: Efficient transformer for high-resolution image restoration Code 2022 CVPR Maxim: Multi-axis mlp for image processing Code 2022 CVPR Uformer: A general u-shaped transformer for ima...
>Feature Representation Learning with MLP Wide&Deep learning.是一个生成模型.Wide learning对应单层的感知机,通过获取直接的历史信息来获取"memorization";Deep learning对应的是多层感知机,通过抽象以及深层次的特征表示来获取"generalization".部署这个模型需要进行特征工程,选择好的特征来获取其"memorization"以及"general...
4.1Survey on Deep Fuzzy Systems This survey will follow two stages to review the DFS for regression applications. First, the DFS will be categorized according to its structure. Secondly, the models will be categorized according to whether they follow the XAI principles. The structures of deep fuz...
The rest of this survey is organized as follows. Section 2 introduces the paradigm development of visual recognition and several related surveys. Section 3 describes the foundations of VLMs, including widely used deep network architectures, pre-training objectives, and downstream tasks in VLM evaluatio...