I know that the TSS stores the informations about the task which is currently running, in order to allow task switching; but I read also that the task switching is carried out by other software task switching methods. So, how is this structure useful?
Hi all, I am currently working on research project where I am trying to segment glomeruli on histological images. (Glomeruli is this round thing here: https://www.auanet.org/images/education/pathology/normal-histology/renal_corpuscle-figureA_Big.jpg) I have already used regular U-Net implemented with tensorflow/keras, which I customized a bit, and it gave me pretty decent results. Now I would like to use something else and implement it by using pytorch. Since this is really specific problem it is hard to find papers which tackle the same task.
The problem is also lack of labeled data of course. I have 100 labeled images altogether. And those images are not whole microscopic images but rather patches with or without glomeruli. To make most of it I have used different image augmentation techniques of course, but I am not sure if it is worth to use some really deep model, such a ResNet.
It really takes a lot of time to find good model with publicly available code and then implement it for your specific tasks. That is why I don't have luxury to try all architectures I find interesting.
Known approaches which I usually do:
Browsing through: https://paperswithcode.com/
Browsing through different forums, such as fast.ai forum.
Searching with google and google scholar with time frame of last few years and keywords related to my problem.
Are there any other common approaches have while searching for the state of the art for specific problems/domains?
The team is getting clowned by it's fans under a tweet about plans of a "helmet game" crowd gimmick instead of the usual white-out.
So last night on the Real Nosey channel on Roku, I saw an episode of an old reality documentary show called State Parole (originally aired on HDNet in 2007-2008, created by the people who gave us Real Stories of the Highway Patrol back in the '90s). In two back-to-back segments in this particular episode, we found out the parolees these agents arrested were avid VHS collectors.
The second segment of the episode shows the agents searching through a parole violator's bedroom, which was loaded with VHS tapes, CDs and video games. Evidently this guy didn't have transportation to report to the parole office like he was supposed to, so he opted to laze around and play Tony Hawk on his PlayStation 2. You'll notice the eclectic mix of major motion pictures on the VHS shelves, along with several South Park episodes released on VHS in the show's early years. Another shelf is loaded with tapes of in-home TV recordings of various shows and movies (one of them being The Sopranos according to one of the agents searching the room). But there's one thing I also noticed--with all those VHS tapes in that room, where's the VCR?
The third and final segment of the episode shows agents searching another parole violator's bedroom where the guy apparently opts to hide his stash of VHS porno movies under his bed. According to the agent perusing the tape labels, the suspect was in possession of such titles as "Tugboat," "Springtime Flying" and "Once Upon a _______" (something the agent opted not to finish saying on camera because he knew it would be bleeped out). I could be wrong, but I don't know that many porno shops were still selling movies on VHS in 2007. The guy evidently kept some of these tapes in a DirecTV receiver box that he hid under his bed. Apparently the adult channels available on DirecTV weren't good enough for him.
Here's a link to the episode itself on Nosey.
https://preview.redd.it/foddz9jt2t581.png?width=1920&format=png&auto=webp&s=9d2fe87444d5d3663da3335c0810a2f4be733434
https://preview.redd.it/sdh6gyit2t581.png?width=1920&format=png&auto=webp&s=3ea549448c99089eef1f340de3a15a879f4e632d
https://preview.redd.it/e7ci93jt2t581.png?width=1920&format=png&auto=webp&s=e55651
... keep reading on reddit β‘
I wanted to create a state task that firedΒ when the battery is between 80 to 85%Β ,
will the task fire continuosly every second or will it fire once and then stop.
Introduced: Sponsor: Sen. Martin Heinrich [D-NM]
This bill was referred to the Senate Committee on Energy and Natural Resources which will consider it before sending it to the Senate floor for consideration.
Sen. Martin Heinrich [D-NM] is a member of the committee.
This full segment of the wives stating how annoyed they are when Kody stays over more than a couple days and how much sunnier life is when Kody isn't there? Lol. I know the egomaniac in him is embarrassed they told the whole world he isn't all that. π€π€π€π€π€π€
I usually have problem focusing on my programming tasks. Though I have listed all the action items and know how to do them, I often sit in front of my computer and feel like slacking off. I always feel like I am eating a frog when I do the task unless I can enter flow state. But entering flow state is not easy, I often miss the deadline. I have been repeating this failure over and over.
Recently, I have started to learn which activities can induce my flow state and which ones I should avoid. I have discussed this with my non-programmer friends. They don't understand what I am saying. They don't have problem focusing on their work, and think I am just a lazy guy finding an excuse to avoid working.
So I want to know your opinion. Is my problem (that I cannot start working without the flow state) common among programmers or is it an individual problem and not related to programming specifically?
Hi all, I am currently working on research project where I am trying to segment glomeruli on histological images. (Glomeruli is this round thing here: https://www.auanet.org/images/education/pathology/normal-histology/renal_corpuscle-figureA_Big.jpg) I have already used regular U-Net implemented with tensorflow/keras, which I customized a bit, and it gave me pretty decent results. Now I would like to use something else and implement it by using pytorch. Since this is really specific problem it is hard to find papers which tackle the same task.
The problem is also lack of labeled data of course. I have 100 labeled images altogether. And those images are not whole microscopic images but rather patches with or without glomeruli. To make most of it I have used different image augmentation techniques of course, but I am not sure if it is worth to use some really deep model, such a ResNet.
It really takes a lot of time to find good model with publicly available code and then implement it for your specific tasks. That is why I don't have luxury to try all architectures I find interesting.
Known approaches which I usually do:
Browsing through: https://paperswithcode.com/
Browsing through different forums, such as fast.ai forum.
Searching with google and google scholar with time frame of last few years and keywords related to my problem.
Are there any other common approaches have while searching for the state of the art for specific problems/domains?
