Primae segmentationis ovi fertilizati mammaliani stationes. Diagramma: z.p., zona pellucida; p.gl., corpora polaria. Stationes: a, duae cellulae; b, quattuor cellulae; c, octo cellulae; d, e, statio morulae.
Morula (a moro) est embryo in prima vitae statione, qui in cellulis (blastomeris appellatis) in globo solido intra zonam pellucidam contento consistit.[1][2]
Morula a blastocyste differt quia morula (dies a tribus ad quattuor post fertilizationem) est massa sedecim cellularum in forma sphaerica consistens, sed blastocystis (a quattuor ad quinque dies post fertilizationem) cavum intra zonam pellucidam habet, cum massa cellulari interiori. Morula, si intacta et continenter inserta, blastocystis denique fiet.[3]
Index
1Nexus interni
2Notae
3Bibliographia
4Nexus externi
Nexus interni
Blastocoele
Blastula
Endometrium
Syncytium
Trophoblastus
Trophoblastus intermedius
Notae |
↑Boklage 2009:217.
↑The Early Embryology of the Chick (UNSW Embryology).
↑The Morula and Blastocyst (Endowment for Human Development).
Bibliographia |
Boklage, Charles E. 2009. How New Humans Are Made: Cells and Embryos, Twins and Chimeras, Left and Right, Mind/Self/Soul, Sex, and Schizophrenia. World Scientific. ISBN 9789812835130. Google Books.
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
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This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
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I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...
