Now you can understand USA amateur radio callsigns
#hamradio #map #ft8
π¦π: https://twitter.com/9k2gv/status/1618261802785345536
| homepage | https://journal.robbi.my |
| PGP key | https://keybase.io/robbinespu/pgp_keys.asc |
| QRZ | https://www.qrz.com/db/9W2NSP |
Now you can understand USA amateur radio callsigns
#hamradio #map #ft8
π¦π: https://twitter.com/9k2gv/status/1618261802785345536
The ID-52E is a VHF/UHF dual band handportable Amateur radio with D-STAR and FM dual mode functions. If you would like more details about this radio including links to brochures, manuals and video overview, visit: https://icomuk.co.uk/ID-52E-Dual-Band-D-STAR-Digital-Transceiver/Handheld_Amateur_Radio_Ham
π¦π: https://twitter.com/Icom_UK/status/1618216644727435280
The ID-52E is a VHF/UHF dual band radio with D-STAR and FM dual mode functions. The ID-52E supports conventional FM communications as well as D-STAR simplex, repeater, regional, and worldwide calls over the D-STAR Internet gateway. With the ID-52E, you can call a friend in another city, or even internationally through D-STAR repeaters, with digital clear audio. In addition, the ID-52E can send digital voice with data, text messages, GPS location information and pictures.
Open-source, hackable amateur radio board #SOCORAD32 for walkie-talkie and data communication applications, Available on @[email protected]
https://www.tecnohub.org/2023/01/open-source-hackable-amateur-radio.html
π¦π: https://twitter.com/finexpofficial/status/1618928967557472256
π http://kerja-IT.com is live β job board for tech jobs in Malaysia.
It scrape jobs from sites like lever(.co), greenhouse(.io) maukerja, hiredly, and more β daily!
Looking for kerja IT? β http://kerja-IT.com
π¦π: https://twitter.com/afrieirham_/status/1618545378303045632
A summary of the different API types π
π¦π: https://twitter.com/Rapid_API/status/1618247043826212866
Final destination siellllllll batang besi tetiba melayang tembus cermin dekat seat penumpangβ¦wtf scary
π¦π: https://twitter.com/IniAlalalannn/status/1614238508671209474
Kisah benar.
π¦π: https://twitter.com/amende_sial/status/1617150199646007302
When subtracting from a number with a lot of zeros, it may be easier to subtract one from both numbers, then subtract.
π¦π: https://twitter.com/howie_hua/status/1615800684397629440
7 Langkah Memperbaiki Kewangan 2023
1. Letakkan matlamat
2. Bina mindset
3. Buat plan tindakan
4. Tingkatkan pendapatan
5. Urus wang dan belanja
6. Bina aset: Simpan & Labur
7. Pertahanan aset: Sedekah, Takaful, Cukai & Pusaka
π¦π: https://twitter.com/afyanIFP/status/1612974405382209539
Accurate Pose Estimation Via WiFi Signals
"our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches, by utilizing WiFi signals as the only input"
arxiv: https://arxiv.org/abs/2301.00250
π¦π: https://twitter.com/nearcyan/status/1615229929825656835
Advances in computer vision and machine learning techniques have led to significant development in 2D and 3D human pose estimation from RGB cameras, LiDAR, and radars. However, human pose estimation from images is adversely affected by occlusion and lighting, which are common in many scenarios of interest. Radar and LiDAR technologies, on the other hand, need specialized hardware that is expensive and power-intensive. Furthermore, placing these sensors in non-public areas raises significant privacy concerns. To address these limitations, recent research has explored the use of WiFi antennas (1D sensors) for body segmentation and key-point body detection. This paper further expands on the use of the WiFi signal in combination with deep learning architectures, commonly used in computer vision, to estimate dense human pose correspondence. We developed a deep neural network that maps the phase and amplitude of WiFi signals to UV coordinates within 24 human regions. The results of the study reveal that our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches, by utilizing WiFi signals as the only input. This paves the way for low-cost, broadly accessible, and privacy-preserving algorithms for human sensing.