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1,551 to 1,560 of 5,197 Results
Resting_20230920-101207_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 1.6 MB - MD5: 6f89a99ff200d3aa573127f98b2e7f9f
Resting_20230922-140841_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 1.6 MB - MD5: 6d1ab70cccf100ba1cb8a4d457f6feed
Resting_20230925-150438_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 1.5 MB - MD5: 5c66ab56e991de548fc32f644ba700a6
Resting_20230926-100939_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 1.6 MB - MD5: cd08de22cbe381f8cc92f4fbf897aa52
Resting_20231005-100611_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 1.5 MB - MD5: 437632f88d0a7f33cff0a70436142bc5
Resting_20231006-130115_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 1.5 MB - MD5: 6ad2d5ec112825bcb3fc7649635f45b5
Kai Keng ANG(Nanyang Technological University)
Oct 9, 2024
Replication Data for: ReVersion: Diffusion-Based Relation Inversion from Images
Oct 8, 2024 - S-Lab for Advanced Intelligence
Huang, Ziqi; Wu, Tianxing; Jiang, Yuming; Chan, Kelvin C. K.; Liu, Ziwei, 2024, "Replication Data for: ReVersion: Diffusion-Based Relation Inversion from Images", https://doi.org/10.21979/N9/UWSAXU, DR-NTU (Data), V1
A replication of the ReVersion Benchmark, for the paper "ReVersion: Diffusion-Based Relation Inversion from Images".
FunQA: Towards Surprising Video Comprehension
Oct 8, 2024 - S-Lab for Advanced Intelligence
Xie, Binzhu; Zhang, Sicheng; Zhou, Zitang; Li, Bo; Zhang, Yuanhan; Hessel, Jack; Yang, Jingkang; Liu, Ziwei, 2024, "FunQA: Towards Surprising Video Comprehension", https://doi.org/10.21979/N9/SMR703, DR-NTU (Data), V1
Surprising videos, e.g., funny clips, creative performances, or visual illusions, attract significant attention. Enjoyment of these videos is not simply a response to visual stimuli; rather, it hinges on the human capacity to understand (and appreciate) commonsense violations dep...
Octopus: Embodied Vision-Language Programmer from Environmental Feedback
Oct 8, 2024 - S-Lab for Advanced Intelligence
Yang, Jingkang; Dong, Yuhao; Liu, Shuai; Li, Bo; Wang, Ziyue; Jiang, Chencheng; Tan, Haoran; Kang, Jiamu; Zhang, Yuanhan; Zhou, Kaiyang; Liu, Ziwei, 2024, "Octopus: Embodied Vision-Language Programmer from Environmental Feedback", https://doi.org/10.21979/N9/9EIB8X, DR-NTU (Data), V1
Large vision-language models (VLMs) have achieved substantial progress in multimodal perception and reasoning. Furthermore, when seamlessly integrated into an embodied agent, it signifies a crucial stride towards the creation of autonomous and context-aware systems capable of for...
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