CV160 [2023-2] 백승우 - AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention is either applied in conjunction with convolutional networks, or used to rep arxiv.org 0. Abstract 트랜스포머 아키텍처는 자연어 처리 작업의 사실상의 표준이 되었지만, 컴퓨터 비전.. 2024. 1. 30. [2023-2] 주서영 - EEG2IMAGE: Image Reconstruction from EEG Brain Signals EEG2IMAGE: Image Reconstruction from EEG Brain Signals Reconstructing images using brain signals of imagined visuals may provide an augmented vision to the disabled, leading to the advancement of Brain-Computer Interface (BCI) technology. The recent progress in deep learning has boosted the study area of synth arxiv.org GitHub - prajwalsingh/EEG2Image: EEG2IMAGE: Image Reconstruction from EEG Br.. 2024. 1. 24. [2023-2] 김경훈 - Latent Consistency Models: Synthesizing High-Resolution Images wi 원본 논문 링크 : https://arxiv.org/abs/2310.04378 Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step InferenceLatent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-resolution images. However, the iterative sampling process is computationally intensive and leads to slow generation. Inspired by Consistency Models (song et al.), we proparxiv.org PD.. 2024. 1. 23. [2023-2] 양소정 - U-Net: Convolutional Networks for Biomedical Image Segmentation https://arxiv.org/pdf/1505.04597.pdf Abstract사용 가능한 주석이 달린 샘플을 보다 효율적으로 사용하기 위해, 하나의 데이터를 여러 데이터처럼 사용하는 전략(data augmentation)을 제시함정확한 localization을 가능하게 하는 대칭 확장 path로 구성됨이러한 네트워크는 적은 수의 이미지에서 end-to-end로 학습될 수 있음그 결과, 성능은 ISBI challenge for segmentation of neuronal structures in electron microscopic stacks에서 이전 최고 방법(a sliding-window convolutional network)을 능가함 ExtraConvolutional Neural Network.. 2024. 1. 8. 이전 1 ··· 35 36 37 38 39 40 다음
