TC-RK3566 Quisque ornare 1: High perficientur CPU
TC-RK3566 Highlights 2: New generation (3rd Gen) Rockchip ISP
TC-RK3566 Highlight 3: Validus multimedia decode/encode facultatem
TC-RK3566 Highlight 4: Integrated efficient RKNN AI processing unit
TC-RK3566 Quisque ornare 1: High perficientur CPU
Nova architectura ARMA et processus progressus altiorem effectum et potentiam efficientiam producit
TC-RK3566 Highlights 2: New generation (3rd Gen) Rockchip ISP
usque ad
Munus potens HDR manifestat imaginem sub backlight vel fortes condiciones lucis
Support dual channel simultaneous zooming output
Munus cancellationis sonitus, ita ut imago sub humili condiciones levis etiam delicata sit
Support defogging functionem, perspicere potest etiam in obducto
Suscipe lateralem correctionem LDCH ad tollendam corruptelam a sensore lens
TC-RK3566 Highlight 3: Validus multimedia decode/encode facultatem
Support 4KP60 H.264/H.265/VP9 et aliis formatis HD decodingis
Support simultaneum decoding multiplicium video fontium
Support HDR10, praestantia observantia in colore et range dynamica
Support imago post-processus, deinterrelinquens, denoising, color amplificationis, augendae resolutio
Support 1080p 60fps H.264 et H.265 forma modum translitterandi
Support dynamicam frenum rate, frame rate, resolutio commensuratio
TC-RK3566 Highlight 4: Integrated efficient RKNN AI processing unit
NPU cum 0.8TOPs computandi potestatem
Accelerator hardware retis embedded neural, subsidium INT8, INT16, FP16 operationem efficientem
NPU ferramentum paternum sustinet technologias sicut antecedens bus, quantitatis canalis, et nulla transiliens
Suscipe lossless compressionem INT8, INT16, FP16 retis neural parametris
Core NPU convolutionem ordinariam sustinet, profunditatem convolutionem separabilem, deconvolutionem, convolutionem foraminis, stratum plene connexum et stratum ponens.
NPU caudices interni includunt operationes multiplicationes addendi, activitatem, LUT unitates conversionis et praecisionem, et sustentaculum constructionis iacuit consuetudo.
Exemplar unum-click conversionem sustine, subsidium Caffe/TensorFlow/TF-Lite/ONNX/PyTorch/Keras/Darknet amet compage exempla