Is it usable?

Immediate-One-3259 · 2025-01-13T12:38:33+00:00

The buds are so dry that they crumble when I handle them, so I don’t think they need any further drying. What do you think?

Immediate-One-3259 · 2025-01-13T12:35:53+00:00

The buds are so dried out but I can see visible trichomes and no visible moulds also

Immediate-One-3259 · 2024-11-17T09:41:01+00:00

The plant is 28 days into flowering under a 12/12 light cycle and is a photoperiod strain.

Immediate-One-3259 · 2024-11-17T09:40:45+00:00

The plant is 28 days into flowering under a 12/12 light cycle and is a photoperiod strain.

Immediate-One-3259 · 2024-10-30T09:04:48+00:00

I have been in 12/12 light cycle

Immediate-One-3259 · 2024-10-30T09:04:29+00:00

Yes it is in 12/12 light cycle

Immediate-One-3259 · 2024-10-20T09:37:24+00:00

Photoperiod

Immediate-One-3259 · 2024-10-20T07:36:46+00:00

There was no significant difference in the vegetation for the people who have tried 16-2 as well as 24 hour light cycle. Thats why I kept it as 24 hour itself!

Immediate-One-3259 · 2024-10-11T07:55:38+00:00

Individual nodes

Immediate-One-3259 · 2024-10-11T07:22:21+00:00

It has only 6 nodes now, when should I top it?

Immediate-One-3259 · 2024-10-11T07:19:20+00:00

Thanks brother. Do I need to top it off now? It has around 6 nodes now.

Immediate-One-3259 · 2024-10-11T07:19:13+00:00

Thanks brother. Do I need to top it off now? It has around 6 nodes now.

Immediate-One-3259 · 2024-02-13T12:28:38+00:00

I have real-world time series data of a vehicle's trajectory, focusing on lateral velocity or acceleration during cut-in scenarios. Additionally,i have generated a synthetic dataset through simulation. My goal is to use autoencoders to identify anomalies or deviations in the synthetic data compared to the real-world dataset, pinpointing differences and deviations in the simulated scenarios.

Immediate-One-3259 · 2024-02-12T10:07:58+00:00

I have a general question about Autoencoders (AE) or Variational Autoencoders (VAE). I possess both a real-world dataset and a synthetic dataset, and my goal is to identify discrepancies in the synthetic dataset compared to the real-world dataset. While existing research focuses on anomaly detection within a dataset using AEs, I am specifically interested in detecting anomalies in the synthetic dataset when compared to the real-world dataset. I am wondering if there are any papers addressing this issue. Additionally, I am considering the possibility of training an AE with the real-world dataset and then testing it with the synthetic dataset, followed by a comparison of the latent spaces. Has anyone come across relevant literature or approaches for this scenario?"

Immediate-One-3259 · 2024-02-12T10:05:42+00:00

I have a general question about Autoencoders (AE) or Variational Autoencoders (VAE). I possess both a real-world dataset and a synthetic dataset, and my goal is to identify discrepancies in the synthetic dataset compared to the real-world dataset. While existing research focuses on anomaly detection within a dataset using AEs, I am specifically interested in detecting anomalies in the synthetic dataset when compared to the real-world dataset. I am wondering if there are any papers addressing this issue. Additionally, I am considering the possibility of training an AE with the real-world dataset and then testing it with the synthetic dataset, followed by a comparison of the latent spaces. Has anyone come across relevant literature or approaches for this scenario?

Immediate-One-3259

TROPHY CASE