#imageanalysis — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #imageanalysis, aggregated by home.social.
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Registration is open!
Want to better validate your #AI methods in #imageanalysis?
Join our 3-part online workshop on June 3, 9 & 25 at 9-12 PM.
Learn to choose metrics, quantify uncertainty & assess the robustness of rankings.
⏳ Register by May 31 👉 https://bit.ly/Validating-AI-for-Image-Analysis
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Registration is open!
Want to better validate your #AI methods in #imageanalysis?
Join our 3-part online workshop on June 3, 9 & 25 at 9-12 PM.
Learn to choose metrics, quantify uncertainty & assess the robustness of rankings.
⏳ Register by May 31 👉 https://bit.ly/Validating-AI-for-Image-Analysis
-
Registration is open!
Want to better validate your #AI methods in #imageanalysis?
Join our 3-part online workshop on June 3, 9 & 25 at 9-12 PM.
Learn to choose metrics, quantify uncertainty & assess the robustness of rankings.
⏳ Register by May 31 👉 https://bit.ly/Validating-AI-for-Image-Analysis
-
Registration is open!
Want to better validate your #AI methods in #imageanalysis?
Join our 3-part online workshop on June 3, 9 & 25 at 9-12 PM.
Learn to choose metrics, quantify uncertainty & assess the robustness of rankings.
⏳ Register by May 31 👉 https://bit.ly/Validating-AI-for-Image-Analysis
-
Registration is open!
Want to better validate your #AI methods in #imageanalysis?
Join our 3-part online workshop on June 3, 9 & 25 at 9-12 PM.
Learn to choose metrics, quantify uncertainty & assess the robustness of rankings.
⏳ Register by May 31 👉 https://bit.ly/Validating-AI-for-Image-Analysis
-
Doing #AI for #imageanalysis? Learn how to validate your results properly:
1️⃣Select appropriate performance metrics
2️⃣Quantify model performance uncertainty
3️⃣Assess the robustness of model comparisons🗓️ June 3 | 9 | 25, 9-12
Registration opens May 6 👉 https://bit.ly/Validating-AI-for-Image-Analysis
Instructors: Annika Reinke, Helmholtz Imaging, DKFZ & Evangelia Christodoulou, DKFZ
This course is organized in cooperation with HIDA.
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Doing #AI for #imageanalysis? Learn how to validate your results properly:
1️⃣Select appropriate performance metrics
2️⃣Quantify model performance uncertainty
3️⃣Assess the robustness of model comparisons🗓️ June 3 | 9 | 25, 9-12
Registration opens May 6 👉 https://bit.ly/Validating-AI-for-Image-Analysis
Instructors: Annika Reinke, Helmholtz Imaging, DKFZ & Evangelia Christodoulou, DKFZ
This course is organized in cooperation with HIDA.
-
Doing #AI for #imageanalysis? Learn how to validate your results properly:
1️⃣Select appropriate performance metrics
2️⃣Quantify model performance uncertainty
3️⃣Assess the robustness of model comparisons🗓️ June 3 | 9 | 25, 9-12
Registration opens May 6 👉 https://bit.ly/Validating-AI-for-Image-Analysis
Instructors: Annika Reinke, Helmholtz Imaging, DKFZ & Evangelia Christodoulou, DKFZ
This course is organized in cooperation with HIDA.
-
Doing #AI for #imageanalysis? Learn how to validate your results properly:
1️⃣Select appropriate performance metrics
2️⃣Quantify model performance uncertainty
3️⃣Assess the robustness of model comparisons🗓️ June 3 | 9 | 25, 9-12
Registration opens May 6 👉 https://bit.ly/Validating-AI-for-Image-Analysis
Instructors: Annika Reinke, Helmholtz Imaging, DKFZ & Evangelia Christodoulou, DKFZ
This course is organized in cooperation with HIDA.
-
Doing #AI for #imageanalysis? Learn how to validate your results properly:
1️⃣Select appropriate performance metrics
2️⃣Quantify model performance uncertainty
3️⃣Assess the robustness of model comparisons🗓️ June 3 | 9 | 25, 9-12
Registration opens May 6 👉 https://bit.ly/Validating-AI-for-Image-Analysis
Instructors: Annika Reinke, Helmholtz Imaging, DKFZ & Evangelia Christodoulou, DKFZ
This course is organized in cooperation with HIDA.
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
-
Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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Pipeline release! nf-core/lsmquant v1.0.0 - 1.0.0 - Excited Squid!
A pipeline for processing and analysis of light-sheet microscopy images.
Please see the changelog: https://github.com/nf-core/lsmquant/releases/tag/1.0.0#3dunet #imageanalysis #imageprocessing #lightsheetmicrocopy #segmentation #stitching #nfcore #openscience #nextflow #bioinformatics
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How Do You Find an Illegal Image Without Looking at It?
https://mahmoud-salem.net/the-invisible-shield
#HackerNews #illegalcontent #digitalprivacy #imageanalysis #cybersecurity
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How Do You Find an Illegal Image Without Looking at It?
https://mahmoud-salem.net/the-invisible-shield
#HackerNews #illegalcontent #digitalprivacy #imageanalysis #cybersecurity
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How Do You Find an Illegal Image Without Looking at It?
https://mahmoud-salem.net/the-invisible-shield
#HackerNews #illegalcontent #digitalprivacy #imageanalysis #cybersecurity
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How Do You Find an Illegal Image Without Looking at It?
https://mahmoud-salem.net/the-invisible-shield
#HackerNews #illegalcontent #digitalprivacy #imageanalysis #cybersecurity
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How Do You Find an Illegal Image Without Looking at It?
https://mahmoud-salem.net/the-invisible-shield
#HackerNews #illegalcontent #digitalprivacy #imageanalysis #cybersecurity
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The image in question is not outdated. A thorough comparison of distance, edges, sky, and surrounding walls confirms its relevance. #ImageAnalysis #OSINT
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The image in question is not outdated. A thorough comparison of distance, edges, sky, and surrounding walls confirms its relevance. #ImageAnalysis #OSINT
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Image analysis reveals enhanced light levels, gear in mid-retraction, and visible slime lights. #ImageAnalysis #OSINT
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🔬 Registration is open for our pilot Introduction to napari Workshop!
napari is a powerful open-source image viewer for scientific data analysis in Python. This hands-on workshop will get you exploring multi-dimensional datasets fast.
✅ Only $20 USD
✅ Limited to 20 people
✅ Perfect for biologists, imaging specialists & data scientistsTwo workshops at two different times.
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🔬 Registration is open for our pilot Introduction to napari Workshop!
napari is a powerful open-source image viewer for scientific data analysis in Python. This hands-on workshop will get you exploring multi-dimensional datasets fast.
✅ Only $20 USD
✅ Limited to 20 people
✅ Perfect for biologists, imaging specialists & data scientistsTwo workshops at two different times.
-
🔬 Registration is open for our pilot Introduction to napari Workshop!
napari is a powerful open-source image viewer for scientific data analysis in Python. This hands-on workshop will get you exploring multi-dimensional datasets fast.
✅ Only $20 USD
✅ Limited to 20 people
✅ Perfect for biologists, imaging specialists & data scientistsTwo workshops at two different times.
-
🔬 Registration is open for our pilot Introduction to napari Workshop!
napari is a powerful open-source image viewer for scientific data analysis in Python. This hands-on workshop will get you exploring multi-dimensional datasets fast.
✅ Only $20 USD
✅ Limited to 20 people
✅ Perfect for biologists, imaging specialists & data scientistsTwo workshops at two different times.
-
🔬 Registration is open for our pilot Introduction to napari Workshop!
napari is a powerful open-source image viewer for scientific data analysis in Python. This hands-on workshop will get you exploring multi-dimensional datasets fast.
✅ Only $20 USD
✅ Limited to 20 people
✅ Perfect for biologists, imaging specialists & data scientistsTwo workshops at two different times.
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Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
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https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
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https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
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#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI -
Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
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https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
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https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
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#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI -
Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
--
https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
--
https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
--
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI -
Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
--
https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
--
https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
--
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI -
Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
--
https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
--
https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
--
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI -
What would you align sets of multiple (~20) large (2-4 Gb) #microscopy images?
For smaller subset images ImageJ plugins for transformations based on SIFT landmark correspondence work well. However standard ImageJ (bioformats) file handling doesn’t cope well with such large files. For plugins handling large file manipulation (BigData family) or chunked (e.g. zarr) storage in turn I don’t know how to implement SIFT (or similar) - e.g. for BigWarp I can only find manual landmark annotation, i.e. no option to create landmarks via other plugins.
My images are iterative fluorescence whole slide scans of the same slide with a constant nuclear stain and varying other stains. There is some x/y shift and rotation as well as warping - nothing major, but I need nearly pixel perfect alignment (e.g. QuPath+Warpy worked well on larger images but was too imprecise).
Stitching happens on the fly during imaging and I’m not sure I can extract the tiles faithfully, so the ASHLAR pipeline didn’t seem applicable. I’ve seen VALIS recommended, but implementation seemed daunting and since the nuclear stain provides reasonable fiducial points the workflow seemed an overkill.Ideally I would want a scripted solution as this has to scale up to hundreds of such sets eventually and downstream processing is in python+R anyhow.
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What would you align sets of multiple (~20) large (2-4 Gb) #microscopy images?
For smaller subset images ImageJ plugins for transformations based on SIFT landmark correspondence work well. However standard ImageJ (bioformats) file handling doesn’t cope well with such large files. For plugins handling large file manipulation (BigData family) or chunked (e.g. zarr) storage in turn I don’t know how to implement SIFT (or similar) - e.g. for BigWarp I can only find manual landmark annotation, i.e. no option to create landmarks via other plugins.
My images are iterative fluorescence whole slide scans of the same slide with a constant nuclear stain and varying other stains. There is some x/y shift and rotation as well as warping - nothing major, but I need nearly pixel perfect alignment (e.g. QuPath+Warpy worked well on larger images but was too imprecise).
Stitching happens on the fly during imaging and I’m not sure I can extract the tiles faithfully, so the ASHLAR pipeline didn’t seem applicable. I’ve seen VALIS recommended, but implementation seemed daunting and since the nuclear stain provides reasonable fiducial points the workflow seemed an overkill.Ideally I would want a scripted solution as this has to scale up to hundreds of such sets eventually and downstream processing is in python+R anyhow.
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What would you align sets of multiple (~20) large (2-4 Gb) #microscopy images?
For smaller subset images ImageJ plugins for transformations based on SIFT landmark correspondence work well. However standard ImageJ (bioformats) file handling doesn’t cope well with such large files. For plugins handling large file manipulation (BigData family) or chunked (e.g. zarr) storage in turn I don’t know how to implement SIFT (or similar) - e.g. for BigWarp I can only find manual landmark annotation, i.e. no option to create landmarks via other plugins.
My images are iterative fluorescence whole slide scans of the same slide with a constant nuclear stain and varying other stains. There is some x/y shift and rotation as well as warping - nothing major, but I need nearly pixel perfect alignment (e.g. QuPath+Warpy worked well on larger images but was too imprecise).
Stitching happens on the fly during imaging and I’m not sure I can extract the tiles faithfully, so the ASHLAR pipeline didn’t seem applicable. I’ve seen VALIS recommended, but implementation seemed daunting and since the nuclear stain provides reasonable fiducial points the workflow seemed an overkill.Ideally I would want a scripted solution as this has to scale up to hundreds of such sets eventually and downstream processing is in python+R anyhow.
-
What would you align sets of multiple (~20) large (2-4 Gb) #microscopy images?
For smaller subset images ImageJ plugins for transformations based on SIFT landmark correspondence work well. However standard ImageJ (bioformats) file handling doesn’t cope well with such large files. For plugins handling large file manipulation (BigData family) or chunked (e.g. zarr) storage in turn I don’t know how to implement SIFT (or similar) - e.g. for BigWarp I can only find manual landmark annotation, i.e. no option to create landmarks via other plugins.
My images are iterative fluorescence whole slide scans of the same slide with a constant nuclear stain and varying other stains. There is some x/y shift and rotation as well as warping - nothing major, but I need nearly pixel perfect alignment (e.g. QuPath+Warpy worked well on larger images but was too imprecise).
Stitching happens on the fly during imaging and I’m not sure I can extract the tiles faithfully, so the ASHLAR pipeline didn’t seem applicable. I’ve seen VALIS recommended, but implementation seemed daunting and since the nuclear stain provides reasonable fiducial points the workflow seemed an overkill.Ideally I would want a scripted solution as this has to scale up to hundreds of such sets eventually and downstream processing is in python+R anyhow.
-
What would you align sets of multiple (~20) large (2-4 Gb) #microscopy images?
For smaller subset images ImageJ plugins for transformations based on SIFT landmark correspondence work well. However standard ImageJ (bioformats) file handling doesn’t cope well with such large files. For plugins handling large file manipulation (BigData family) or chunked (e.g. zarr) storage in turn I don’t know how to implement SIFT (or similar) - e.g. for BigWarp I can only find manual landmark annotation, i.e. no option to create landmarks via other plugins.
My images are iterative fluorescence whole slide scans of the same slide with a constant nuclear stain and varying other stains. There is some x/y shift and rotation as well as warping - nothing major, but I need nearly pixel perfect alignment (e.g. QuPath+Warpy worked well on larger images but was too imprecise).
Stitching happens on the fly during imaging and I’m not sure I can extract the tiles faithfully, so the ASHLAR pipeline didn’t seem applicable. I’ve seen VALIS recommended, but implementation seemed daunting and since the nuclear stain provides reasonable fiducial points the workflow seemed an overkill.Ideally I would want a scripted solution as this has to scale up to hundreds of such sets eventually and downstream processing is in python+R anyhow.
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Eerie… but then again context is everything. Google has access to a huge amount of information in the images and exif information if available. Correlating all of this across its huge user base provides possibilities we cannot even imagine.
These companies and their tools already know more of us than we know about ourselves. We are the product.
Ever realized why we need rules and regulations around privacy?
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Eerie… but then again context is everything. Google has access to a huge amount of information in the images and exif information if available. Correlating all of this across its huge user base provides possibilities we cannot even imagine.
These companies and their tools already know more of us than we know about ourselves. We are the product.
Ever realized why we need rules and regulations around privacy?
-
Eerie… but then again context is everything. Google has access to a huge amount of information in the images and exif information if available. Correlating all of this across its huge user base provides possibilities we cannot even imagine.
These companies and their tools already know more of us than we know about ourselves. We are the product.
Ever realized why we need rules and regulations around privacy?
-
Eerie… but then again context is everything. Google has access to a huge amount of information in the images and exif information if available. Correlating all of this across its huge user base provides possibilities we cannot even imagine.
These companies and their tools already know more of us than we know about ourselves. We are the product.
Ever realized why we need rules and regulations around privacy?
-
Eerie… but then again context is everything. Google has access to a huge amount of information in the images and exif information if available. Correlating all of this across its huge user base provides possibilities we cannot even imagine.
These companies and their tools already know more of us than we know about ourselves. We are the product.
Ever realized why we need rules and regulations around privacy?
-
I have two open positions in my lab at the Advanced Light Microscopy Unit Centre for Genomic Regulation (CRG):
- Imaging Scientist (permanent position. Deadline 11th Nov.) https://recruitment.crg.eu/content/jobs/position/imaging-scientists-advanced-light-microscopy-unit-almu
- Entry-Level Imaging Scientist (12 months fixed-term position. Deadline 18th Nov.) https://recruitment.crg.eu/content/jobs/position/entry-level-imaging-scientist-advanced-light-microscopy-unit-almu
If you have any questions don’t hesitate to reach out.
Boosts appreciated.
#getfedihired #fedihire #jobSearch #jobposting #Microscopy #Optics #ImageAnalysis
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I have two open positions in my lab at the Advanced Light Microscopy Unit Centre for Genomic Regulation (CRG):
- Imaging Scientist (permanent position. Deadline 11th Nov.) https://recruitment.crg.eu/content/jobs/position/imaging-scientists-advanced-light-microscopy-unit-almu
- Entry-Level Imaging Scientist (12 months fixed-term position. Deadline 18th Nov.) https://recruitment.crg.eu/content/jobs/position/entry-level-imaging-scientist-advanced-light-microscopy-unit-almu
If you have any questions don’t hesitate to reach out.
Boosts appreciated.
#getfedihired #fedihire #jobSearch #jobposting #Microscopy #Optics #ImageAnalysis